MCP server · Kimetsu

kimetsu

Kimetsu ships its MCP server inside the kimetsu binary: `kimetsu mcp serve` is a local stdio server that hosts (Claude Code, Codex, Cursor, Pi, OpenClaw, Gemini CLI) launch per project, exposing ~28 kimetsu_* tools over a per-project SQLite brain. `kimetsu setup --host ` / `kimetsu plugin install ` write the host-native MCP config (.mcp.json + .claude/settings.json for Claude Code, .codex/ for Codex, openclaw.json, a Pi extension) plus the hook wiring. There is NO provider-hosted endpoint: the only HTTP MCP surface is Kimetsu Remote (beta), a separate `kimetsu-remote` server binary an operator runs on their own machine (bearer tokens, one brain per repo at https:///mcp/). The tool list below is transcribed from the Interfaces page; inputSchema per tool requires a local `kimetsu mcp serve` + tools/list, which this pass did not run.

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Provider: Kimetsu Type: Documentation link Transport: stdio Host: kimetsu.dev

Documentation

https://kimetsu.dev/docs/how-kimetsu-works/interfaces

Documentation link · transport stdio

Tools

kimetsu_brain_context — Retrieve a context bundle (returns skipped true when nothing relevant, at zero overhead)
kimetsu_brain_record — Capture a lesson; runs semantic dedup
kimetsu_brain_status — Brain health + memory counts
kimetsu_brain_insights — Effectiveness analytics over recent runs
kimetsu_brain_memory_add — Direct memory create
kimetsu_brain_memory_list — Direct memory list
kimetsu_brain_memory_top — Top memories
kimetsu_brain_memory_search — Memory search
kimetsu_brain_memory_proposals — Review pending proposals
kimetsu_brain_memory_accept — Accept a pending proposal
kimetsu_brain_memory_reject — Reject a pending proposal
kimetsu_brain_memory_invalidate — Retire a memory
kimetsu_brain_memory_blame — Per-run citation attribution
kimetsu_brain_memory_conflicts — List ingest conflicts
kimetsu_brain_conflict_resolve — Settle an ingest conflict
kimetsu_brain_prune — List (or invalidate) net-negative memories
kimetsu_brain_model_list — Inspect available embedding models
kimetsu_brain_model_set — Switch the embedding model
kimetsu_brain_reindex — Re-embed the brain after a model change
kimetsu_brain_ingest_repo — Index repo files + manifests
kimetsu_benchmark_context — Task-aware playbook
kimetsu_benchmark_record_outcome — Outcome recording for the task-aware playbook
kimetsu_bridge_* — Skill registry discovery, import, export, sync (a family of tools; individual names not enumerated on the docs page)
kimetsu_skills_search — Search the cross-harness skill registry
kimetsu_brain_cite — Record that a memory materially helped
kimetsu_brain_answer — Grounded, cited answer composed from memory (local model)
kimetsu_brain_config_show — Show the effective configuration (named in the configuration docs)

About MCP

The Model Context Protocol (MCP) is an open protocol Anthropic introduced for connecting LLM-based agents to external tools and data sources. Providers publish MCP servers that expose their API surface as structured, discoverable tools — an MCP-compatible client (Claude Desktop, Cursor, Cline, Continue, etc.) can connect to the server and call its tools without any per-provider integration code.

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MCP server

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Tools for mcp servers

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