MCP server · emem
emem
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Endpoint
Hosted endpoint · transport streamable-http
Connect
This is a remote MCP server — point an MCP client at the endpoint URL. Clients with native remote support (Claude, Cursor, VS Code, …):
# mcp client config (e.g. .mcp.json / mcp settings)
{
"mcpServers": {
"emem-dev": {
"url": "https://emem.dev/mcp"
}
}
}
For stdio-only clients (older Claude Desktop, etc.), bridge with mcp-remote:
# Add to claude_desktop_config.json
{
"mcpServers": {
"emem-dev": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://emem.dev/mcp"]
}
}
}
If the server requires authentication, add the provider's token/header (e.g. an X-API-Key) per its docs. A quick reachability check:
curl -i -X POST https://emem.dev/mcp \
-H "Content-Type: application/json" -H "Accept: application/json, text/event-stream" \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'
Tools
emem_tools— The map of emem's tool surface, and the only tool you need to find the rest: the working loop in the order you walk it (name, ground, cite, resolve, verify, check for drift), then every other tool grouped by the question it answers, each wiemem_locate— Mint the canonical, vendor-neutral address (cell64) for a real-world place: the shared spatial identity every agent resolves to identically, so two models refer to the same ground instead of two descriptions of it. Also returns the topic-gremem_ask— Single-shot free-text answer about a real-world location, backed by signed satellite/elevation/water/built-up receipts. Forwards a place mention plus a question; runs the locate → recall → algorithm chain server-side; returns one packaged eemem_hunt— Event-discovery sweep: pick an event keyword (algal_bloom, deforestation, flood_extent, wildfire, urban_heat_island, methane_plume, landslide, drought, soil_salinity, crop_stress, water_turbidity, oil_slick) plus a region (free-text name or polygon_bbox). The responder geocodes the region, fans out across up to 32 sampled cells, recalls each event's primary scalar input band, and returns the top 8…emem_eudr_dds— Produce a Due Diligence Statement per Regulation (EU) 2023/1115 for one or more plots. Each plot carries operator-supplied geometry (GeoJSON Polygon for >4 ha, Point for ≤4 ha non-cattle per Article 2(28)), country of production (ISO3), Combined Nomenclature code (HS-6+), and quantity in kg. The endpoint applies the regulation's 10 % canopy / 0.5 ha / 5 m height forest definition (Article 2(4)) us…emem_spi— Compute the Standardized Precipitation Index (McKee et al. 1993) at a cell: fit a gamma distribution to the same-window precipitation-accumulation history, then standardize the current accumulation to a z-score and map it to a drought class (extreme/severe/moderate drought … normal … wet). Supply `precip_history_mm` + `current_accumulation_mm` directly, or omit them to read the stored `weather.pre…emem_burn_severity— Compute the differenced Normalized Burn Ratio (dNBR = NBR_pre − NBR_post; Key & Benson 2006) and map it to the USGS burn-severity classes (unburned / low / moderate-low / moderate-high / high). Supply `nbr_pre` + `nbr_post` (pin the scenes bracketing the fire date) for a correct result, or omit both to use the two most-recent stored `indices.nbr` scenes (older=pre, newer=post) as a coarse estimate…emem_rice_ch4— Estimate seasonal CH4 emissions from rice cultivation per IPCC 2019 Refinement Eq 5.1: integrate the daily emission factor over the cultivation period with water-regime scaling (SFp pre-season, SFo organic amendment) and an optional Yan-2005 Q10 temperature modifier. `cultivation_period_days` and the regional `efc_kg_ch4_ha_day` (Table 5.11) are REQUIRED, the endpoint refuses to guess a global def…emem_deforestation_alert— Composite deforestation-alert score: `alert_score = 0.5·clamp01(ndvi_drop/0.30) + 0.5·clamp01(embedding_change/0.20)`, where `ndvi_drop = max(0, ndvi_modis_baseline − ndvi_now)` and `embedding_change = 1 − cos(tessera_latest, tessera_prev)`. Each half degrades INDEPENDENTLY and honestly: if a band is missing, that half is dropped AND the output is renamed so a half-score can never be mistaken for …emem_sar_forest_disturbance— Cloud- and night-independent Sentinel-1 C-band confirmation of forest disturbance. Intact forest scatters VV strongly + stably (canopy volume scattering); clearing collapses that term so VV backscatter DROPS ~3-5 dB. Samples VV at a baseline-year July-1 anchor and the latest scene, reports `vv_drop_db = baseline − recent` and a `disturbed` flag when the drop ≥ 3 dB (Reiche et al. 2018, RSE 204:147…emem_triple_consensus— Three-encoder change ensemble: compute the cosine change between the two most-recent DISTINCT vintages for each of the Clay, Prithvi, and Tessera embeddings at the cell, then vote each encoder's change against `consensus_threshold` (registry default 0.15). Returns each encoder's change magnitude, its vote, and the consensus verdict (how many of the three agree change happened). Two caveats ride ev…emem_change_attribution— The first runnable surface of the change decomposition Δz = Δ_env + Δ_sensor + Δ_geo + Δ_encoder + ε: a per-term evidence LEDGER for the readout change at a cell, with NO numeric split. `observed` carries the Tessera year-over-year embedding change. `terms.env` carries label-free index pairs (NDVI, NBR, NDWI) with raw deltas and both fact cids, evidence a future estimator would read. `terms.sensor…emem_band_raster— Return a native-resolution Sentinel-2 window over a bounding box as a FIELD, not a set of points: the pixels become one content-addressed grid artifact (deterministic f32 encoding; fetch the bytes at the returned artifact url, Cache-Control immutable), and what the receipt attests is the DERIVATION, never a byte pipe. A persisted derivation record pins the chosen scene (id, asset, capture time, cl…emem_raster_resolve— Resolve emem:raster:: : : back to its signed derivation record and the artifact's status. Every claim in the token binds to the signed record before anything dereferences, the same rule fact tokens follow: the cid must be a band_raster@1 derivation and the token's aoi_cid, band, and tslot must each match the record's own body, so a real derivation_cid cannot be … emem_band_cube— Mint an emem:cube: token: a Sentinel-2 field over an AOI ACROSS TIME. A world model is a field over an area across time, and emem:raster: names only one time-slice, so a 4D world's time scrub had no token to anchor. This mints one band_raster member per target date, each an independent, resolvable emem:raster: derivation, then signs a cube record binding the ordered set. It is NOT new pixels: line…emem_band_composite— Mint a signed, cloud-masked median composite over a date window as a raster-shaped field: the clean, gap-filled texture a world model actually drapes, rather than one cloudy scene. It reads every Sentinel-2 scene in [start_date, end_date] over the bbox, masks each per pixel by its SCL scene-classification class (default reject {0,1,3,8,9,10}: no-data, saturated, cloud shadow, cloud, cirrus; snow 1…emem_cube_resolve— Resolve emem:cube:: : .. : back to its signed cube record and the ordered member emem:raster: tokens. Same fail-closed rule as emem_raster_resolve: the cid must be a band_cube@1 derivation, the token's aoi_cid, band, and tslot range must each match the signed record, and cube_cid is recomputed from the record's members so an altered membership is ref… emem_raster_bundle— Mint an emem:rasterset: token: a signed manifest binding 2..64 already-minted emem:raster: field tokens (any mix of band_raster / s2_median_composite / dem_raster / embedding_raster) into ONE citeable thing. The composition primitive a world model or a compliance report needs when it must cite one token that points at every signed layer at once - the RGB ground composites, the DEM geometry, the en…emem_raster_bundle_resolve— Resolve emem:rasterset:: back to its signed manifest and verify it. Fail-closed like every field-token resolve: the cid must be a raster_bundle@1 derivation, bundle_cid is recomputed from the record's ordered members and matched against BOTH the token and the record (any mismatch is a typed 409, refusing an altered or forged membership), and every member emem:raster: to… emem_terrain— Compute three standard DEM terrain indices from one 3×3 Copernicus-DEM (copdem30m.elevation_mean) neighbourhood at a cell: Horn (1981) slope in degrees, Riley (1999) Terrain Ruggedness Index (TRI = sqrt(Σ(Z_centre−Z_i)²)), and Weiss (2001) Topographic Position Index (TPI = Z_centre − mean(neighbours); positive = ridge, negative = valley). The 8 neighbour cell64s are derived by perturbing the cell'…emem_region_similarity— Answer 'how alike are these two places?' Mean-pool the 128-D GeoTessera embedding across each region's cells to get a centroid, then return the cosine similarity in [-1,1] (+1 = identical landscape, 0 = unrelated). Each region is {place} | {polygon_bbox} | {cells}. CPU-fetched embeddings, no GPU sidecar needed. Surfaces how many cells in each region actually carried a vector (coverage). When to u…emem_embedding_centroid— Mean-pool the 128-D GeoTessera embedding over a region's cells: centroid = (1/N) Σ v_i, plus the L2-normalised centroid and a content-addressed centroid_cid. The building block region_similarity composes. Region is {place} | {polygon_bbox} | {cells}. NaN dims are averaged over their finite contributors. CPU-only. When to use: Call when you need one representative embedding vector for an area, to …emem_embedding_diversity— Quantify how varied a region's landscape is: diversity = (1/(N(N-1))) Σ_{iemem_neighborhood_consistency— Score how much a cell looks like its surroundings: consistency = (1/8) Σ cosine(centre, neighbour_i) over the 8 immediate cell64 neighbours, plus outlier_score = 1 − consistency. High consistency = the cell blends in (Tobler's First Law); high outlier_score = it stands out, an edge, a fresh clearing, a built patch in farmland. CPU-only GeoTessera embeddings. When to use: Call to flag a cell that …emem_state— Get one dense numeric fingerprint that summarises everything known about a place, ready to feed into similarity search, a classifier, or clustering. Two views: `encoder` returns a single AI-model embedding (128-D Tessera, 1024-D Clay, 1024-D Prithvi); `cube` returns the full 1792-D vector concatenated across every band, with a per-band coverage manifest. When to use: Call this when the user wants…emem_state_multi— Get the place's fingerprint from several AI models at once (`geotessera`, `clay_v1`, `prithvi_eo2`, `galileo`) in one call, returned as a per-model map. Each model is tried independently; any that can't produce a vector here show up under `missing` with a reason instead of failing the whole request. When to use: Call this when the user wants a second (or third) opinion on what a place looks like,…emem_state_diff— Vector delta between the same cell at two tslots: returns the per-element residual, its L2 norm (scalar change-magnitude), the cosine between the two source vectors (orientation drift), and both source fact CIDs so the agent can quote both attestations as evidence. When to use: Call when the user asks 'how much did X change between A and B' for a foundation embedding at one place. Pass `tslot_a` …emem_memory_token— Mint a citation handle, `emem:fact:: ` (or `: `), that any agent or LLM resolves to the byte-identical signed object. The antidote to referential drift on the value side: hand this one string to another agent inst search— Search emem's signed corpus and return results shaped as citations: each entry is one signed fact, with an `id` to dereference, a `title` naming band, place and the value as signed, and a stable `url` serving those bytes. Takes a place namefetch— Dereference an id from `search`: the reading in one line, then the signed body it came from, the URL serving those bytes, and metadata naming cell, band, signing time and key. Takes an `emem:fact:` citation, a bare fact_cid, or an `emem:celemem_memory_token_resolve— Parse a `emem:fact:: ` citation handle and return the reading it cites. `value`, `unit`, `band` and `kind` are on the response at the TOP level, alongside the full signed `fact` body they were lifted from. Saves the agent f emem_echo_verify— Grade a value you are about to emit against the signed fact your citation points at. Returns `matches` and, when it does not, the `drift` between what you were about to say and what emem holds. This is the step that turns a transcription eremem_derive— Register a value YOU computed from facts this responder holds, and get back a citeable `emem:fact:` token whose lineage terminates in emem-signed measurements. The registered fact names its parents by CID, so a stranger walks the DAG down to signed sensor data instead of trusting your summary. Requires an ed25519 `attester` block. What the responder signs is narrow and it says so on the response: …emem_derive_list— List the derivations registered by one ed25519 key, optionally filtered to a cell (and then a band). The explicit opt-in read for caller-registered derivatives: they hold no canonical key, so no default read path returns them, and this is the only way to enumerate one rather than resolve it by token. When to use: Call to enumerate your own derivations (pass your pubkey_b32), or to inspect what a …emem_memory_bundle— Compose N (cell, band, tslot?) triples into ONE signed envelope. Each triple runs through the standard auto-materialize recall path; the resulting fact_cids are bundled into a content-addressed envelope and the responder signs over the fullemem_memory_bundle_resolve— Parse a `emem:bundle:` token and return the signed bundle envelope: every citation (cell, band, resolved_tslot, fact_cid, memory_token), the receipt, the responder pubkey, and the deduped flat cells[] / fact_cids[] arrays. Returns 404 with a typed code when the responder does not hold the bundle. When to use: Call when an agent receives an `emem:bundle:` token from another agent (or e… emem_entity— Give a real-world object (a bridge, a farm plot, a river, a named place) a single, shared, content-addressed identity that any agent resolves the same way. Returns an `entity_token` (`emem:entity:`) plus a signed receipt that at emem_entity_resolve— Find the objects agents have bound a phrasing to, ranked by INDEPENDENT corroboration, never arrival order. Each candidate carries `asserted_by`, `disputed_by`, `independent_attesters` and `corroboration` (`single_key` | `multiple_independeemem_entity_link— Record a signed, ATTRIBUTED claim that a label or external id (GERS / OSM / Wikidata) denotes an existing object, or with `stance: "disputes"` that it does not. A shared-space write: it changes what other agents resolve, so it is stored witemem_memory_view— Read the contents of a memory file at `/memories/` or list a directory when the path ends with `/`. Optional `view_range: [start, end]` slices a 1-indexed inclusive line range out of the file. Mirrors the `view` verb in Anthropic's context-management-2025-06-27 memory tool spec. Reads are public: no key, no account, and every stored memory on this responder is world-readable, including files… emem_memory_create— Write a memory file at `/memories/` with the supplied `file_text`. Overwrites if the file exists AND your key owns the path; a write over someone else's file is refused, not merged. Persists to sled, content-addresses the bytes (`file_cid`), and signs the write so the operation carries a verifiable receipt. Mirrors the `create` verb in Anthropic's context-management-2025-06-27 memory tool sp… emem_memory_str_replace— Replace `old_str` with `new_str` in the named memory file. Fails (no partial write) when `old_str` is absent or matches more than once. Writes a new content-addressed `file_cid` and signs the receipt. Mirrors the `str_replace` verb in Anthropic's context-management-2025-06-27 memory tool spec. WRITES ARE SIGNED, NOT ANONYMOUS: supply `attester: {pubkey_b32, sig_b32}`, an ed25519 signature over bla…emem_memory_insert— Insert `new_str` after the given 1-indexed line in the named memory file. `insert_line: 0` inserts at the top. Writes a new `file_cid` and signs the receipt. Mirrors the `insert` verb in Anthropic's context-management-2025-06-27 memory tool spec. WRITES ARE SIGNED, NOT ANONYMOUS: supply `attester: {pubkey_b32, sig_b32}`, an ed25519 signature over blake3("emem.memory_write|| | … emem_memory_delete— Delete a memory file at `/memories/`. When the path ends with `/`, every file beneath the directory is removed. Updates the path index but leaves prior content-addressed blobs in place (the audit history is append-only). Mirrors the `delete` verb in Anthropic's context-management-2025-06-27 memory tool spec. WRITES ARE SIGNED, NOT ANONYMOUS: supply `attester: {pubkey_b32, sig_b32}`, an ed255… emem_memory_supersede— Point one of your notes at the note that replaces it. Readers of the superseded path then receive `superseded_by` and a `_superseded` banner, so a withdrawn claim stops resolving as though it were current. This is redirection, not deletion: the original bytes are unchanged and still resolve by their own cid, because the log is append-only and issued receipts must stay verifiable. The replacement m…emem_memory_rename— Move (rename) a memory file from `old_path` to `new_path`. Both paths must stay under `/memories/`; `new_path` must not already exist. The file_cid is preserved (no re-sign) so the prior receipt still binds the bytes. Mirrors the `rename` verb in Anthropic's context-management-2025-06-27 memory tool spec. WRITES ARE SIGNED, NOT ANONYMOUS: supply `attester: {pubkey_b32, sig_b32}`, an ed25519 signat…emem_memory_list_by_kind— List memory files by their typed `kind` (episodic | semantic | procedural | resource). Optional path prefix narrows the scan; results are sorted by signed_at descending. The kind taxonomy follows the CoALA / LangMem / MIRIX agent-memory ontology: `episodic` = observations of events, `semantic` = durable learned facts, `procedural` = playbooks, `resource` = generic durable scratchpad (default for b…emem_memory_search— Semantic search over /memories/* file contents using BGE-base-en-v1.5 (768-D, L2-normalised) backed by a Lance partition (`memory_text_index_d768.lance`). Matches paraphrases, "rainfall in March" finds "precipitation observed in spring" without an exact substring match. Returns ranked hits with similarity in [0,1], 200-char snippets around the best-matching chunk, and the signing receipt's path / …emem_corpus_state_stats— Signed snapshot of corpus liveness: distinct_cells, distinct_bands, facts_scanned, top per-band counts, manifest CIDs. Same payload that backs /v1/stream's corpus.state tick (signed). Use this for a one-shot poll instead of holding an SSE connection. When to use: Call when an agent needs a single liveness reading to surface in a dashboard, attach to a report, or decide whether to refresh local ca…emem_benchmark— Hand-verified evaluation items for grading an agent against the responder. Returns {items[], grader_url}. Submit answers (cell64 or fact_cid per item) to POST /v1/benchmark/grade for per-item scores. Items today: elevation recall, NDVI, find_similar neighbours. When to use: Call once at agent-onboarding time (or in CI) to fetch the canonical task list, then have the agent answer each item using i…emem_recall— Read the signed facts at a canonical address (cell64); auto-materializes on a miss for any band with a registered materializer. A fact_cid names one signed attestation, so a recalled fact is citeable and re-verifiable rather than a paraphraemem_recall_polygon— Recall facts across every cell inside a place's polygon (single signed envelope). Closes the place-name-drift gap for wide features (parks, lakes, regions). When to use: Call when the user names a wide feature (national park, river basin, country, large urban area) where one cell is too small. Pass `place` and the geocoder will fan out across the polygon, or pass `polygon_bbox` directly if you ha…emem_field_boundaries— Per-field agricultural-boundary polygons from the Fields of The World global product (~3.17B fields, 241 countries, 10 m resolution, CC-BY-4.0). Returns a GeoJSON FeatureCollection with the polygon geometries, FIBOA-compatible properties, and a planar `area_m2` per field, plus provenance (source CID, provider URL, license, attribution). When to use: Call when the user asks about farms, fields, pa…emem_query_region— Query facts over a region (single cell or list of cells), optionally aggregated per band. A bbox is SAMPLED, not enumerated: the sampler walks addresses inside the box and returns only the ones already materialized, so at any human-sized region (a district, a city) it commonly returns an empty aggregate even when a warm cell sits inside the box. That is the sampler being honest, not a miss. Measur…emem_compare— Compare two cells: cosine similarity over shared vector bands + per-band scalar deltas. When to use: Call when the user asks 'how similar is X to Y', 'compare these two places', or wants a difference vector. Returns a single cosine score and per-band deltas. Example arguments: {"a":"damO.zb000.xUti.zde78","b":"damO.zb000.xUto.sisA"}emem_compare_bands— Compare two bands at the same cell. Scalar pair → metric=delta, value=b-a. Vector pair (equal dim) → metric=cosine + per-dim delta. Returns a signed receipt naming both source fact CIDs. When to use: Call when the user wants cross-source consistency at one place ('does Cop-DEM agree with GMRT here?'), cross-vintage drift ('how did the embedding change between 2017 and 2024 at this cell?'), or any…emem_find_similar— k-NN over the corpus by cell embedding or inline vector. Returns `neighbours` ordered nearest-first, each with `cell64`, `score` and the `band` scanned, plus a signed receipt over the vectors read. Scoring is `mode`: cosine is exact fp32; hemem_trajectory— Time series for one (cell, band) over an inclusive [start, end] tslot window. Returns only what's already attested; it does NOT trigger materialization. For historical backfill use `emem_backfill`. When to use: Call when the user asks 'how did X change over time' for a band that already has multiple historical tslots seeded. IMPORTANT differences from `emem_recall`: (1) trajectory does NOT auto-m…emem_diff— Compute a DerivativeFact (delta) between a band's values at two tslots. Memory algebra: the `diff` operation (https://emem.dev/docs/model.html). For a time-varying band the response also carries an unsigned `phenology` advisory: the day-of-year of each tslot, their gap, and a `caution` when the two dates sit at different points in the seasonal cycle, because that delta mixes phenology with real ch…emem_compare_same_doy— Compare a band at the SAME day-of-year across several years, the honest way to measure year-over-year change on a seasonal band. For each year it finds the signed facts bracketing the target day-of-year and linearly interpolates to it, and EXCLUDES years that cannot be bracketed (with a typed reason) rather than extrapolating. This is the primitive the phenology advisory on emem_diff points at: co…emem_memory_contradictions— Surface where the corpus DISAGREES with itself (algebra: competing evidence). When two or more independent sources signed different values for the same place + band + time, this returns that disagreement with a 0–1 severity score and citatiemem_edges_recall— Read temporal knowledge-graph edges (subj --pred--> obj, valid over [valid_from, valid_to)), bi-temporally filtered, in EITHER direction. Forward (`subj`, direction="out", the default): edges originating at a subject fact. Reverse (`obj`, direction="in"): edges pointing AT a fact, what disagrees-with / supersedes / relates-to it. Returns a signed list of edges plus the distinct neighbour fact CIDs…emem_fetch— Fetch a fact by its content-address (CID). Returns the full signed Primary or Absence fact, the same body served by REST `/v1/facts/{cid}`. Closes the citation loop: any fact_cid surfaced by recall, materialize, attest, or verify can be re-resolved by another agent without REST. When to use: Call whenever you have a `fact_cid` (e.g. from `emem_recall`'s response, an `emem_attest` receipt, an `eme…emem_backfill— Materialize and sign every per-tslot fact for one (cell, band) inside a [start_unix, end_unix] window. Returns a signed list of (tslot, fact_cid, status) for each step. Slow but possible, one upstream fetch per tslot, capped by `max_facts`. READ THE COUNT CAREFULLY: `steps[].tslot` is the REQUESTED slot, not the slot the fact landed in. A signed fact carries the SCENE's own tslot, so consecutive r…emem_heat_solve— Forward-step 2-D explicit finite-difference solver for the heat equation ∂u/∂t = α∇²u over a 3×3 cell stencil centred on `cell`. Reads `modis.lst_day_8day` (Land Surface Temperature) at the centre and 8 cell64 neighbours, integrates N hours ahead under a CFL-stable timestep, returns a signed forecast. Real PDE rollout, not a decay-scoring heuristic. When to use: Use when the user wants a short-ho…emem_wave_solve— Forward-step 1-D explicit finite-difference solver for the shallow-water wave equation ∂²u/∂t² = c²∂²u/∂x² with c² = g·h, where depth h comes from `gmrt.topobathy_mean` along the seaward gradient. Models how an offshore swell of height H_s and period T propagates toward `coastal_cell`. Returns a signed forecast of arrival height + time + depth + phase-speed profiles, all under a CFL-stable timeste…emem_jepa_predict— Predict next-month NDVI at a cell using a constrained JEPA-pattern AR(2) seasonal predictor. Reads up to 24 past months of `indices.ndvi`, fits a closed-form predictor `y_{t+1} = α·(lag-12 NDVI or recent mean) + β·(last + slope) + γ·recent_mean`, returns the prediction clamped to NDVI's physical range. Coefficients (α=0.6, β=0.3, γ=0.1) are NOT learned, they're fixed from the agricultural-NDVI lit…emem_jepa_predict_v2— Predict the next-step value of 4 environmental scalars at a cell (`indices.ndvi`, `modis.lst_day_8day`, `modis.lst_night_8day`, `cams.pm25`) using a small learned dynamics MLP. Reads up to K=6 most-recent attested lags per band, runs them through an ONNX dynamics head (~200k params, CPU-fast), and returns a per-band {value, confidence, n_real_lags, via}. The receipt's `model` block carries `model_…emem_verify— Verify a structured claim against a cell's facts. Returns verdict + evidence CIDs + signed receipt. When to use: Call when the user asks a yes/no question about a cell ('is the NDVI > 0.7 here', 'has this been deforested'), or when downstream code wants citable evidence for a logical predicate. Example arguments: {"cell":"damO.zb000.xUti.zde78","claim":{"band":"indices.ndvi","op":"gt","value":0.…emem_bands— Active band ontology (offsets, dims, tempo, privacy). When to use: Call once at session start to learn the band registry, every other primitive's `band` argument MUST come from this list. Example arguments: {}emem_functions— Active function registry (derivation recipes). When to use: Call when you need to know which derivative ops are available for `emem_diff` or how a band is computed from upstream sources. Example arguments: {}emem_sources— Active source-connector registry (URL templates, providers, licenses). When to use: Call when you need to inspect which upstream EO providers are wired (Copernicus DEM, JRC GSW, ESA WorldCover, etc.), useful for license attribution in agent answers. Example arguments: {}emem_schema— Active CDDL/JSON schema bundle by CID. When to use: Rarely needed at chat time. Useful for offline verification of receipts / attestations against the exact schema version a responder used. Example arguments: {}emem_errors— Stable error code catalog. When to use: Call to enumerate the wire-stable error codes, useful when the LLM wants to programmatically branch on responses. Example arguments: {}emem_manifests— Active manifest CIDs (bands / functions / sources / schema). When to use: Call to learn which exact registry versions a responder is serving. Cite these CIDs alongside any answer where reproducibility matters. Example arguments: {}emem_capabilities— Live capability snapshot of the responder's GPU sidecar, extensions[] (e.g. gpu, clay-v1.5, prithvi-eo2), cuda_available, models_loaded[], healthy, last_polled_unix_s. Refreshed every 30 s by a background poller; reads are constant-time. When to use: Call before scheduling a GPU-heavy plan (Clay / Prithvi / Galileo embeddings, foundation-anchored algorithms) so the agent knows whether the GPU tie…emem_grid_info— Active grid encoding: cell64 ground resolution, lat/lng axis sizes, DGGS lineage. When to use: Call once at session start (or when the user asks about cell resolution / 'how big is a cell'). Returns the actual ground resolution today (~9.54 m × 9.55 m square at the equator (lat 21 bits × lng 22 bits, matching Sentinel-1/Sentinel-2 native pixel pitch). The cell64 bit layout reserves a resolution-t…emem_cells_in_bbox— Enumerate every cell64 whose centre falls in a bounding box, paged, in stable row-major order (north row first, then west column first). Pure geometry: it reads no facts and signs no receipt, because the answer is a deterministic function of the bbox and the active grid that anyone can reproduce. It walks the integer lat/lng grid directly, so it never skips or double-counts a cell the way a float-…emem_coverage_matrix— Per-band live status, what data is alive AND auto-materializable, with history bounds, tempo cadence, and the responder pubkey that signs the band. When to use: Call BEFORE `emem_recall` when you don't know which bands answer at this responder. For each band returns `has_materializer` (true → an empty recall will auto-fetch+sign, no seeding needed), `facts_count` (how many cells already cached), …emem_materializers— Auto-fetch registry: which bands the responder will materialize on a recall miss, the upstream provider, license, value shape, and history bounds. When to use: Call once at session start (alongside `emem_bands` and `emem_coverage_matrix`) to learn which bands answer for ANY cell on Earth without seeding. Each entry declares `upstream_scheme`, `upstream_endpoint`, `derivation_fn_key`, `value_kind`…emem_data_availability— Temporal catalog: for every materializable band the upstream-of-record window the data genuinely covers, the temporal `kind` (static | annual_snapshot | annual_stack | time_series | now_only | per_release), tempo seconds, upstream wire path, and whether `emem_backfill` is meaningful. When to use: Call before `emem_backfill` or any historical recall to check whether a band has a meaningful past at…emem_algorithms— Content-addressed dictionary of composition recipes, formulas that fuse attested band facts (and embeddings) into derived scores, classifications, and similarity metrics. When to use: Call when the user's question is COMPOSITE (flood risk, urban density, water consensus, change-since-2020) rather than a single band readout. Each entry has `kind` (solo | combined | embedding), the input `bands` (a…emem_explain_algorithm— Per-key drill-down on a single composition recipe, full body (kind, inputs, formula, output, citation, references) for ONE algorithm key. Companion to `emem_algorithms` (which is the catalog). When to use: Call when you already know the algorithm key (from `emem_algorithms`'s catalog or the topic registry) and need its full math. Cheaper than fetching the full catalog when you only need one entry…emem_topics— Topic-grouped registry of every band and algorithm at this responder, plus visual surfaces and the `declared_but_no_materializer_at_this_responder` block (cube slots reserved without a live connector). Single source of truth shared with `/v1/locate`'s `data_at_this_cell` block. When to use: Call when the user's question lives in a topic but they haven't named a specific band, e.g. 'is this place …emem_coverage_map— Live SVG render of the responder's corpus density, returned as a proper MCP EmbeddedResource content block (image/svg+xml), multimodal MCP agents can render it natively. When to use: Call when the user asks 'where do you have data?', 'show me the coverage', or wants a visual brief of the responder's corpus footprint. Returns a 1440×720 Plate-Carrée SVG (1° × 1° bins, log-scale colour, continent e…emem_cell_scene_rgb— True-colour Sentinel-2 L2A RGB thumbnail centred on a cell. PNG returned as a native MCP ImageContent block (mimeType image/png). Pure-Rust pipeline: STAC search + HTTP-Range COG reads + 2-98 percentile stretch + PNG encode. When to use: Call when the user wants a VISUAL of a place, 'show me what this looks like', 'before/after the flood', 'is there a forest here', 'is this developed'. Returns a …emem_cell_geojson— Cell polygon as a native MCP EmbeddedResource (mimeType application/geo+json). Properties carry centre lat/lng, bbox, approx size in metres, and the 8-cell neighbourhood, drop straight into Mapbox / Leaflet / Deck.gl / QGIS without a GIS pipeline. When to use: Call when the agent (or a downstream renderer) needs the cell as geographic geometry, for map overlays, polygon-clipping ops, or feeding a…emem_recall_many— Recall facts across a list of up to 256 cell64 strings in one round-trip. Server fans out per-cell recalls in parallel and returns them under `by_cell.`. NOT one signed envelope: there is no aggregate receipt, and each cell carries its own under `by_cell. .receipt`, so verifying one cell verifies that cell only. Audit a bulk call by verifying each cell's receipt independently. When t… | emem_elevation— One-shot elevation answer that fuses Cop-DEM 30 m (land), GMRT (ocean topobathy), and ESA WorldCover (water mask) into a single signed scalar at a place or coordinate. Returns `elevation_m`, the source actually used, and a `coherence_note` when the two surfaces disagree at the coast. When to use: Use when the user asks 'how high is X' or 'what's the elevation at this lat/lng' and you want the cor…emem_fleet— Per-band satellite-and-sensor fleet inventory, names the upstream platform (e.g. Sentinel-2A/B, MODIS Aqua/Terra, Landsat-8/9), revisit cadence, native resolution, and license for every materialized band. Lets an agent attribute imagery products correctly and pick the right band when revisit cadence matters. When to use: Call when the user asks 'which satellite is this from', 'what's the revisit …emem_substrates— The written admission contract per contributor class (satellite archive, operator constellation, telescope, microscope, CCTV, mobile, drone, robot, industrial machine, fixed sensor): which admission rule applies (recomputable public archive, or complete OS execution trace), which trace layers a device of that class must capture, the measurement grain range, and which profile is the drift anchor. C…emem_trace_verify— Stateless verification of an emem.os_trace.v1 record against a substrate profile: schema, device identity, capture window, per-layer coverage, segment digest chain, merkle trace_root, emitted-output binding, and the device's ed25519 signature. Returns the full verdict with every failed check named (chain_broken, missing_layer, output_unbound, signature_invalid, ...), never just a boolean, so a dev…emem_temporal_route— Turn a time-shaped question into a ready-to-run recall plan: it figures out WHICH bands to pull at WHICH past time windows (e.g. 'the year before the flood', 'last growing season', 'two vintages to compare') so you don't have to compute tslot offsets by hand. Returns the band + lookback + a `purpose` tag for each step. Algebra: valid(M, a): per-band validity from the physics decay kernel, cite_now…emem_verify_receipt— Verify a signed receipt envelope server-side: rebuilds the canonical preimage under the rule the receipt's own `preimage_version` names, runs ed25519 over the embedded key and signature, and returns `{valid, reason, failure_detail, signaturemem_guard_verdict— Run emem-guard's policy pipeline over text you are about to send, against this responder's corpus. Finds every emem: citation, resolves each one, and returns allow or deny with a machine-readable reason: `EMEM-GUARD DENYtoken=emem_guard_selfhost— Returns the full emem-guard self-host skill as markdown, plus the exact build, test and run commands. A node you run needs no account here and no key from us: it generates its own signing key, keeps its own append-only verdict log, verifies what it holds, and cites what it does not. It exposes checkpoints for Anthropic Inference hooks, Claude Code client hooks, MCP tools/call, OpenAI-shaped client…emem_at— One-shot recall of the signed facts at a place's cell64 (or lat/lng); each band carries a citeable fact_cid. Defaults to emem's standard at-a-glance band set; pass `band` / `bands` to override. Polygon-resolved places stay at the centroid by default (`n_cells: 1`) to keep multi-band calls cheap; pass `n_cells: 2..=64` to fan out. When to use: Use when the user names a place and wants the standard…emem_ndvi— Recall the signed Sentinel-2 NDVI fact (indices.ndvi, 10 m native) at a place's canonical cell64, attesting it into the shared memory on a miss. Composes locate → cell64 → recall in one call; the value returns with its citeable fact_cid. When to use: Use when the user names a place (or lat/lng) and just wants the NDVI number. Polygon-resolved places default to a 16-cell fan-out aggregated as mean…emem_air— Recall the signed Copernicus CAMS air-quality facts (PM2.5 + NO2 + O3) at a place's cell64, attesting on a miss. Composes locate → recall → aggregate; each band carries a citeable fact_cid. When to use: Use when the user names a place and asks about air quality, pollution, or emissions exposure. CAMS is the European reanalysis, global coverage, ~0.4° native (resampled). For finer-grained urban PM…emem_lst— Recall the signed MODIS land surface temperature facts (day-8day + night-8day composites, 1 km native) at a place's cell64, attesting on a miss; each carries a citeable fact_cid. When to use: Use when the user asks about surface heat, urban heat island, thermal anomalies, or wants day/night LST. Returns both fluxes so the agent can derive day–night spread. Example arguments: {"place":"Phoenix, A…emem_soil— Recall the signed SoilGrids 250 m profile at a place's cell64 (SOC, pH, clay/sand/silt fractions, bulk density, nitrogen, all at 0–30 cm depth), attesting on a miss; each band carries a citeable fact_cid. When to use: Use when the user asks about soil quality, agricultural suitability, or carbon stocks at a location. Six bands returned in one envelope. Example arguments: {"place":"Bhanu Pratappu…emem_water— Recall the signed surface-water facts at a place's cell64: JRC Global Surface Water recurrence (1984–2021) + Sentinel-1 SAR backscatter (current), attested on a miss and citeable by fact_cid. The pair detects standing water through clouds. When to use: Use when the user asks about flooding, wetlands, surface-water dynamics, or wants a robust water-presence check. JRC alone gives historical baseli…emem_forest— Recall the signed forest facts at a place's cell64: Hansen Global Forest Change (tree cover 2000 baseline + year-of-loss) + ESA WorldCover 2021 land class, attested on a miss; each carries a citeable fact_cid. When to use: Use when the user asks about deforestation, canopy cover, forest loss, or wants a forest-vs-not classification. Hansen gives year-of-loss for any cell with disturbance since 20…emem_weather— Recall the signed met.no/CAMS weather facts at a place's cell64 (2 m temperature + total cloud cover + precipitation + 10 m wind speed), attesting on a miss; each value carries a citeable fact_cid. When to use: Use when the user names a place and asks 'what's the weather' or wants a now-cast snapshot. weather.* bands are now-only (no backfill); for climatology use terraclimate.*. Example argumen…emem_intent— Say what you want in one typed object and get the answer, without choosing a primitive. `type` is a tagged union: it selects the intent AND decides which other fields are read, so send only the fields its row needs. The plan is EXECUTED inemem_log_sth— Fetch the responder-signed tree head (STH) over the whole append-only attestation log: {tree_size, root_b32, signed_at, responder_pubkey_b32, signature_b32}. The signature is ed25519 over a domain-separated preimage, verifiable offline. When to use: Call to pin a cryptographic commitment to the log's current state. Save the STH, then later call emem_log_consistency to prove the log only grew (app…emem_log_inclusion— Return an RFC 6962 inclusion (audit) proof that a log entry is committed under the current signed tree head. Verify offline: the audit path re-derives the STH root from the entry's leaf hash. When to use: Call to prove a specific log entry is in the log. Pass `leaf_index` (0-based position) or `entry_hash` (base32 of the record's blake3). Returns the audit path plus the STH to check it against. …emem_log_consistency— Return an RFC 6962 consistency proof that the tree of size `first` is an append-only prefix of size `second` (defaults to the current size). This is the append-only guarantee: it catches a responder that rewrites or forks history. When to use: Call with `first` = the tree_size of an STH you pinned earlier. Verify the returned proof offline against that STH's root; if the first_root does not match…emem_log_witnesses— List witness co-signatures recorded for tree heads, independent parties that counter-signed a (tree_size, root) claim under their own ed25519 key. Co-signatures let a client detect split-view equivocation. Empty until witnesses submit (submission is a signed write, done off-MCP via POST /v1/log/witness). When to use: Call to see who has independently vouched for the log's history. For each co-sig…emem_reason— The opt-in reasoning tier: grounds your question through emem_ask (deterministic, signed), then has the responder's local model compose a prose answer over that envelope. The prose is model_output and signed:false by construction, it is never evidence; the grounding block beside it (fact_cids + receipt) is. Runs the model greedily (temperature 0) under a per-model single-flight lock, so a cold loa…
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