Server data from the Official MCP Registry
MCP-first agent learning: capture failures, validate lessons, retrieve context, improve.
MCP-first agent learning: capture failures, validate lessons, retrieve context, improve.
Valid MCP server (1 strong, 1 medium validity signals). 1 known CVE in dependencies (0 critical, 1 high severity) Package registry verified. Imported from the Official MCP Registry.
5 files analyzed · 2 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
This plugin requests these system permissions. Most are normal for its category.
Set these up before or after installing:
Environment variable: SUPERMEMORY_STORAGE_PATH
Environment variable: UALL_DATA_DIR
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-yashvanthange-supermemory": {
"env": {
"UALL_DATA_DIR": "your-uall-data-dir-here",
"SUPERMEMORY_STORAGE_PATH": "your-supermemory-storage-path-here"
},
"args": [
"supermemory-agent"
],
"command": "uvx"
}
}
}From the project's GitHub README.
MCP-first agent learning layer for Claude, Cursor, and custom agent workflows.
SuperMemory captures distilled lessons from failures and corrections — not full conversation transcripts — validates them before storage, and improves agents over time through a closed-loop cycle.
pip install supermemory-agent
supermemory-agent --storage .supermemory --transport stdio
Or with uv:
uvx supermemory-agent --storage .supermemory --transport stdio
Latest release: v0.2.4 — wheel + sdist attached on every GitHub Release.
| Component | Description |
|---|---|
| MCP server | 29 tools + 4 resources over stdio (or streamable HTTP) |
| Agent skill | skills/supermemory-agent-learning/SKILL.md — bundled in the PyPI package |
| Python SDK | In-process integration via uall_python |
| REST API | FastAPI server for remote / polyglot clients |
| Storage | Local .supermemory/ files by default; SQLite and PostgreSQL optional |
Everything lives in one repo: MCP server, skills, SDK, REST API, tests, and release packages.
pip install supermemory-agent
After install, bundled skills are at site-packages/skills/supermemory-agent-learning/. Copy to your editor skills folder if needed.
Each release ships installable assets:
pip install https://github.com/YashvantHange/SuperMemory/releases/download/v0.2.4/supermemory_agent-0.2.4-py3-none-any.whl
Browse all versions: github.com/YashvantHange/SuperMemory/releases
git clone https://github.com/YashvantHange/SuperMemory.git
cd SuperMemory
pip install -e ".[dev]"
python -m pytest tests/ -v
Copy examples/cursor.mcp.json to .cursor/mcp.json in your project:
{
"mcpServers": {
"supermemory": {
"command": "supermemory-agent",
"args": ["--storage", ".supermemory", "--transport", "stdio"]
}
}
}
Merge examples/claude_desktop_config.json into:
%APPDATA%\Claude\claude_desktop_config.json
Restart Claude Desktop after saving.
Do not run supermemory-agent alone in a terminal — stdio mode expects JSON-RPC from an MCP client. Pressing Enter in the shell causes a JSON parse error.
# For local HTTP testing only:
supermemory-agent --transport streamable-http
When configured in Cursor or Claude Desktop, the client launches the server automatically over stdio.
| Source | Path |
|---|---|
| Canonical (edit here) | skills/supermemory-agent-learning/ |
| Cursor project | .cursor/skills/supermemory-agent-learning/ |
| Claude Code project | .claude/skills/supermemory-agent-learning/ |
| PyPI install | site-packages/skills/supermemory-agent-learning/ |
After editing skills/, sync copies:
python scripts/sync_skills.py
Mention SuperMemory, agent learning, or MCP memory in chat to load the skill.
retrieve → record_failure → reflect(event_ids) → validate → process_promotions
→ retrieve again → report_outcome
Core rule: capture workflow outcomes and distilled lessons only — never full transcripts. Default retrieval budget: max_tokens=800.
Core (13): retrieve, record_event, record_failure, record_correction, reflect, validate, process_promotions, report_outcome, get_policies, add_policy, add_skill, search_skills, get_skill
Extended UALL (16): learn.run.start, learn.run.event, learn.run.end, learn.store, learn.retrieve, learn.reflect, learn.validate, learn.evaluate, learn.feedback, learn.improvements, learn.analytics, learn.policies, learn.experiment, learn.rollback, learn.skills, learn.telemetry
All tools include MCP safety annotations (readOnlyHint / destructiveHint).
supermemory://policies/activesupermemory://lessons/{lesson_id}supermemory://memory/{lesson_id}/provenancesupermemory://skills/{skill_id}from uall_python import UALLClient
client = UALLClient(storage="file")
with client.run(workflow_id="pdf-pipeline", step="planner", namespace="team:eng") as run:
lessons = run.retrieve(step="planner", max_tokens=800)
run.record_failure(snippet="chose OCR for searchable PDF", tags=["routing"])
run.report_lesson_outcome(lesson_id="lesson_001", used=True, accepted=True, improved=True)
python -m uall_server
Server: http://localhost:8000 — see api/openapi.yaml.
| Tier | Backend | Config |
|---|---|---|
| Default | .supermemory/ JSON files | SUPERMEMORY_STORAGE_PATH or UALL_DATA_DIR |
| Optional | SQLite | UALL_STORAGE_BACKEND=sqlite |
| Enterprise | PostgreSQL | UALL_STORAGE_BACKEND=postgres |
SuperMemory/
├── src/supermemory_mcp/ # MCP server (29 tools, 4 resources)
├── skills/supermemory-agent-learning/ # Agent skill (SKILL.md)
├── packages/uall/ # Core learning engine
├── packages/uall_python/ # Python SDK
├── packages/uall_server/ # REST API
├── examples/ # Cursor + Claude Desktop MCP configs
├── tests/ # 74 tests incl. stdio MCP transport
└── docs/ # Publishing, releases, privacy
python -m pytest tests/ -v
python -m pytest tests/test_mcp_server.py -v # real stdio MCP transport
python -m pytest tests/test_core.py -v # closed-loop integration
| Doc | Purpose |
|---|---|
| docs/GIT_SETUP.md | Fix commit author name/email on GitHub |
| docs/RELEASES.md | Release checklist — every tag ships wheel + sdist |
| docs/PUBLISHING.md | PyPI, MCP Registry, Cursor & Claude directories |
| PRIVACY.md | Privacy policy |
| skills/README.md | Agent skill install paths |
MCP Registry name: io.github.YashvantHange/supermemory
PyPI package: supermemory-agent
MIT — see LICENSE
Be the first to review this server!
by Modelcontextprotocol · Developer Tools
Web content fetching and conversion for efficient LLM usage
by Toleno · Developer Tools
Toleno Network MCP Server — Manage your Toleno mining account with Claude AI using natural language.
by mcp-marketplace · Developer Tools
Create, build, and publish Python MCP servers to PyPI — conversationally.