# Brainfeather

**Canonical:** https://apis.io/providers/brainfeather-com/  
**Website:** https://brainfeather.com/  
**APIs profiled:** 0

Brainfeather provides a long-term memory layer for AI coding agents, capturing durable facts about projects such as stack, conventions, and decisions, and making them available to Claude Code, Cursor and other agents on subsequent runs. This service helps avoid starting from zero each session, offering background fact capture without added latency, shared across connected clients, and includes a Model Context Protocol (MCP) server. Currently in early development and free while in beta.

## Kin Score — 6.0 / 100 (minimal)

Scored 2026-11-06 under rubric 0.27.0.

| Facet | Score |
|---|---|
| Discoverability | 48.2 |
| Contract Quality | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 0.0 |
| Access Clarity | 10.5 |

Regulatory layer — **Horizontal (data, software, accessibility, platform)**: 9.1 (matched via fallback).

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |
| Delegated Identity | no |
| Protected Resource Metadata | no |
| Dynamic Client Registration | no |
| Agentic Commerce | no |
| Pagination Ratio | na |
| Operation Distinctiveness | na |
| MCP Tool Quality | na |

## Access

Unknown — onboarding: unknown, pricing: unknown, trial: no (confidence: low).

## Security (1)

- **Brainfeather Com Domain Security** — TLSv1.3 · HSTS

## Tags

Company, Artificial Intelligence, Memory, Agents, MCP, Beta

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/brainfeather-com/). Scores are computed from the provider's own public artifacts under a published rubric.