
Repomemory
io.github.DanielGuruPublished by GitHub account DanielGuruv1.3.0Updated Oct 24, 2026
Persistent memory for AI coding agents. Hybrid search, auto-session capture, context routing.
The publisher's own server: RepoMemory
Overview
Persistent, searchable project memory for AI coding agents, exposing tools to search, read, write and delete a repo's .context knowledge base.
- What you can do
- Search and orient: hybrid keyword plus semantic search over repo and global context, and a one-call orientation returning index, preferences and recent sessions.
- Read and browse: read full entries with repo-first, global-fallback lookup, and list entries tagged by provenance.
- Write and maintain: record facts, decisions, regressions and preferences with scope routing, and delete stale knowledge.
- Assess risk: report hotspots, hidden coupling and bus factor for the codebase or specific files.
- Capture sessions and git history: session summaries are saved on shutdown and git history can be synced into a changelog.
- When to use it
- Useful when you work on the same codebase across many AI sessions and want agents to stop re-discovering architecture, re-debating settled decisions or re-introducing fixed bugs. It suits teams that want shared, searchable project knowledge instead of a static instruction file.
- Requirements
- Runs locally via npx (Node.js). Setup commands write MCP configuration and rules into tools such as Claude Code, Cursor, Copilot, Windsurf, Cline, Aider and Continue. AI analysis needs a provider API key such as ANTHROPIC_API_KEY, OPENAI_API_KEY, GEMINI_API_KEY or GROK_API_KEY; Cursor setup can skip external keys. Optional embeddings use Gemini or OpenAI keys.
Installation
In SourceWeft
- Open Repomemory in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
repomemory
Your codebase never forgets.
AI agents lose context every session. repomemory fixes that — one command creates a persistent, searchable knowledge base that any AI tool can read, search, and write to.
The Problem
Every time you open a project with Claude Code, Cursor, Copilot, or any AI coding agent:
- It re-discovers your architecture from scratch
- It proposes changes that were already debated and rejected
- It re-introduces bugs that were already fixed
Your CLAUDE.md / .cursorrules helps, but it's static and gets stale.
The Solution
Facts tell agents how things work. Decisions prevent re-debating. Regressions prevent re-breaking. Preferences teach agents how you code.
Quick Start
With an API key (Claude Code, terminal workflows)
One command: sets up global profile, creates .context/, configures Claude Code + Cursor, runs AI analysis, prints CLAUDE.md instructions.
With Cursor (no API key needed)
This installs everything Cursor needs:
- MCP server in
~/.cursor/mcp.json(auto-starts repomemory in every project) - Rules in
.cursor/rules/repomemory.mdc(teaches Cursor's AI to use context) - 6 commands in
.cursor/commands/(run with/in Cursor chat)
Then in Cursor chat, type:
Cursor's own AI scans your repo and populates .context/ via the MCP tools. No external API key required — your Cursor subscription handles it.
Available Cursor commands:
Guided wizard
Walks through provider selection, tool integration, and first analysis. If no API keys are detected, offers a "None — I use Cursor" option that skips external analysis entirely.
Non-interactive (CI-safe)
No prompts when --yes / --defaults / --no-prompt is used.
MCP Server — Agents With Real Memory
The real power is the MCP server. When configured via repomemory setup claude, it auto-starts with Claude Code and gives agents 7 tools:
Sessions are auto-captured on shutdown. Zero config — repomemory setup claude handles everything.
Supported Tools
Cursor users: You don't need any API key. Run
npx repomemory setup cursor, then use/repomemory-analyzein Cursor chat. Cursor's AI does the analysis using the MCP tools — whatever model Cursor is using (it can even switch models mid-task).
Supported Providers
Embeddings (optional, for semantic search): Gemini text-embedding-004 (free, default) or OpenAI text-embedding-3-small. Auto-detected from available API keys.
All Commands
Configuration
.repomemory.json in your repo root (all fields optional):
Custom ignorePatterns and keyFilePatterns are additive — they extend built-in defaults, not replace them.
Why Not Just CLAUDE.md?
repomemory doesn't replace CLAUDE.md — it complements it. CLAUDE.md is for instructions and rules. .context/ holds the knowledge that grows over time.
Contributing
See CONTRIBUTING.md for development setup, testing, and contribution guidelines.
License
MIT
Built for developers who are tired of AI agents forgetting everything between sessions.
Source: README.md at commit b5b9d25
Tools
0Version history
1- v1.3.0LatestSep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts