agents-memory
Ingests OpenAI/ChatGPT session logs and extracts durable rules, facts, and architecture decisions into the local memory store.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@agents-memorysearch memory for the decision on microservices"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
agents-memory
Local markdown memory & cross-agent context engine for AI coding assistants.
One persistent identity, shared across Claude Code, Cursor, Antigravity, and Zed.
Why .agents/memory?
The name agents-memory comes directly from its universal storage standard: .agents/memory.
Global:
~/.agents/memory/stores your persistent identity, stack defaults, durable concepts, and project index.Repository:
<repo>/.agents/memory/stores repo-specific facts, architecture ADRs, and staging inboxes.
While AI vendors fragment their configuration across proprietary stores, .agents/ provides a single, open, vendor-neutral filesystem hub for all agent configurations and shared intelligence.
agents-memory delivers this with a pure Markdown-first architecture:
Local & Offline: Your identity and repo memory live in plain files (
~/.agents/memory/and<repo>/.agents/memory/).Human-Readable & Git-Friendly: Edit with any text editor, diff with git, commit when you want.
Universal MCP Server: Exposes memory tools (
search_memory,add_memory,get_project_memories,distill_batch) to all modern agents.Autonomous Ingest & Distillation: Extracts durable rules and architecture decisions from session logs (OpenAI, Claude, Cursor, Copilot, Antigravity, Pi).
Related MCP server: agent-julia
Architecture & Flow
┌─────────────────────────────────────────────────────────────┐
│ SESSION INGEST │
│ OpenAI Exports · Claude JSONL · Cursor · Antigravity · Pi │
└──────────────────────────────┬──────────────────────────────┘
│ ingest catalog / extract
▼
┌─────────────────────────────────────────────────────────────┐
│ STAGING INBOX │
│ Raw captured bullets & noise-filtered facts │
└──────────────────────────────┬──────────────────────────────┘
│ distill_batch / skill
▼
┌─────────────────────────────────────────────────────────────┐
│ LOCAL MEMORY STORE │
│ ~/.agents/memory/USER.md ~/.agents/memory/PROJECTS.md │
│ ~/.agents/memory/concepts/ <repo>/.agents/memory/ │
└──────────────┬───────────────────────────────┬──────────────┘
│ │
▼ ▼
┌─────────────────────────────┐ ┌─────────────────────────────┐
│ IDE INJECTION │ │ MCP SERVER & CLERK │
│ Cursor Rules · Zed Context │ │ search_memory · add_memory │
│ Antigravity AGENTS.md │ │ Universal Tool Integration │
└─────────────────────────────┘ └─────────────────────────────┘Quickstart
1-Step Setup
pip install agents-memory && agents-memory sync --initScaffolds ~/.agents/memory/, autowires MCP configurations into your installed IDEs, and registers assistant skills.
🤖 Agent-Driven Setup (Zero Friction):
Simply tell your coding agent: "Install and set up agents-memory for me."
The agent installs the package, asks your stack preferences once, fills your USER.md profile, and registers your repositories autonomously.
CLI Reference
Command | Purpose |
| Updates canonical |
| First-time scaffolding, example creation, and host discovery |
| Discovers unregistered local repositories across workspace roots |
| Registers a new repository |
| Indexes local chat transcripts across all supported providers |
| Runs heuristic filters to extract durable facts into staging |
| Ensures no private state leaked into working repository |
Supported Ecosystem
Claude Code: Bound via symlink / canonical
AGENTS.mdand MCP server.Google Antigravity: Integrated via
.gemini/configrules andagents-memoryMCP.Cursor: Automatically injects rules and configures
.cursor/mcp.json.Zed: Configures
context_serversand mirrors assistant skills.VS Code / Copilot: Ingests session history from local state databases.
Also compatible with: Windsurf, Cline, Roo-Code, Aider, Continue.dev, OpenAI ChatGPT, Pi, Goose, and any MCP-compliant AI assistant.
Open ABI Specification
The formal, implementation-agnostic layout specification lives in abi/:
abi/WHY.md— Architecture decisions & why Markdown wins over RAG.abi/LAYOUT.md— Directory taxonomy and path contracts.abi/KINDS.md— Typed memory taxonomy (concepts,facts,decisions).abi/MCP.md— Tool definitions and request/response specifications.abi/INGEST.md— Catalog, extract, and distillation pipeline.abi/INJECTION.md— Host rule injection mechanisms.
Testing & Verification
Run the comprehensive test suite and distillation benchmark:
python tests/run_all_tests.pyLicense
MIT License. See LICENSE for details.
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