SuperMemory

MCP-first agent learning: capture failures, validate lessons, retrieve context, improve.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "supermemory": {
      "command": "uvx",
      "args": [
        "supermemory-agent"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Documentation Overview

SuperMemory

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.

Quick start

Terminal

pip install supermemory-agent
supermemory-agent --storage .supermemory --transport stdio

Or with uv:

bash

uvx supermemory-agent --storage .supermemory --transport stdio

Latest release: v0.2.4 — wheel + sdist attached on every GitHub Release.

What you get

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.

Install

PyPI (recommended)

Terminal

pip install supermemory-agent

After install, bundled skills are at site-packages/skills/supermemory-agent-learning/. Copy to your editor skills folder if needed.

GitHub Release (offline / pinned version)

Each release ships installable assets:

Terminal

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

From source (developers)

bash

git clone https://github.com/YashvantHange/SuperMemory.git
cd SuperMemory
pip install -e ".[dev]"
python -m pytest tests/ -v

Configure MCP

Cursor

Copy examples/cursor.mcp.json to .cursor/mcp.json in your project:

config.json

{
  "mcpServers": {
    "supermemory": {
      "command": "supermemory-agent",
      "args": ["--storage", ".supermemory", "--transport", "stdio"]
    }
  }
}

Claude Desktop

Merge examples/claude_desktop_config.json into:

Code

%APPDATA%\Claude\claude_desktop_config.json

Restart Claude Desktop after saving.

Run manually

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.

bash

# 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.

Agent skills (Cursor + Claude Code)

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:

bash

python scripts/sync_skills.py

Mention SuperMemory, agent learning, or MCP memory in chat to load the skill.

Learning loop

Code

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.

MCP tools (29)

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).

MCP resources (4)

supermemory://policies/active
supermemory://lessons/{lesson_id}
supermemory://memory/{lesson_id}/provenance
supermemory://skills/{skill_id}

Python SDK

server.ts

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)

REST API

bash

python -m uall_server

Server: http://localhost:8000 — see api/openapi.yaml.

Storage

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`

Project layout

Code

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

Tests

bash

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

Docs

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

License

MIT — see LICENSE

Read the full README →View source on GitHub →

Related MCP Servers

View all in Knowledge & Memory View all alternatives

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

Stargazers on the source repository.

Last commit

3mo ago

Most recent push to the default branch.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about SuperMemory

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "supermemory": { "command": "uvx", "args": ["supermemory-agent"] } }

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Technical Specs & Signals

CategoryKnowledge & Memory

4/7 checks healthy over the last 45d

37Quality signal: Fair · 37/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools16/30

Adoption & activity2/15

Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 6d ago via OSV.dev · supermemory-agent (PyPI)

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Explore more

More in 🧠 Knowledge & Memory →Best MCP servers for Memory & Knowledge →Alternatives to SuperMemory →Install in Claude Desktop Install in Cursor Install in VS Code Setup guides for all 13 MCP clients

SuperMemory

MCP-first agent learning: capture failures, validate lessons, retrieve context, improve.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "supermemory": {
      "command": "uvx",
      "args": [
        "supermemory-agent"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Documentation Overview

SuperMemory

MCP-first agent learning layer for Claude, Cursor, and custom agent workflows.

Quick start

Terminal

pip install supermemory-agent
supermemory-agent --storage .supermemory --transport stdio

Or with uv:

bash

uvx supermemory-agent --storage .supermemory --transport stdio

Latest release: v0.2.4 — wheel + sdist attached on every GitHub Release.

What you get

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.

Install

PyPI (recommended)

Terminal

pip install supermemory-agent

After install, bundled skills are at site-packages/skills/supermemory-agent-learning/. Copy to your editor skills folder if needed.

GitHub Release (offline / pinned version)

Each release ships installable assets:

Terminal

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

From source (developers)

bash

git clone https://github.com/YashvantHange/SuperMemory.git
cd SuperMemory
pip install -e ".[dev]"
python -m pytest tests/ -v

Configure MCP

Cursor

Copy examples/cursor.mcp.json to .cursor/mcp.json in your project:

config.json

{
  "mcpServers": {
    "supermemory": {
      "command": "supermemory-agent",
      "args": ["--storage", ".supermemory", "--transport", "stdio"]
    }
  }
}

Claude Desktop

Merge examples/claude_desktop_config.json into:

Code

%APPDATA%\Claude\claude_desktop_config.json

Restart Claude Desktop after saving.

Run manually

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.

bash

# 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.

Agent skills (Cursor + Claude Code)

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:

bash

python scripts/sync_skills.py

Mention SuperMemory, agent learning, or MCP memory in chat to load the skill.

Learning loop

Code

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.

MCP tools (29)

All tools include MCP safety annotations (readOnlyHint / destructiveHint).

MCP resources (4)

supermemory://policies/active
supermemory://lessons/{lesson_id}
supermemory://memory/{lesson_id}/provenance
supermemory://skills/{skill_id}

Python SDK

server.ts

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)

REST API

bash

python -m uall_server

Server: http://localhost:8000 — see api/openapi.yaml.

Storage

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`

Project layout

Code

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

Tests

bash

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

Docs

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

License

MIT — see LICENSE

Read the full README →View source on GitHub →

Related MCP Servers

View all in Knowledge & Memory View all alternatives

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

Stargazers on the source repository.

Last commit

3mo ago

Most recent push to the default branch.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about SuperMemory

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "supermemory": { "command": "uvx", "args": ["supermemory-agent"] } }

AllMCPs Directory Badge

Full Badge Customizer

Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.

Badge Style:

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Markdown (GitHub README)

[![AllMCPs](https://allmcps.com/api/badge/supermemory?style=directory)](https://allmcps.com/mcp/supermemory)

HTML Embed

<a href="https://allmcps.com/mcp/supermemory"><img src="https://allmcps.com/api/badge/supermemory?style=directory" alt="SuperMemory on AllMCPs" /></a>

Technical Specs & Signals

CategoryKnowledge & Memory

4/7 checks healthy over the last 45d

37Quality signal: Fair · 37/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools16/30

Adoption & activity2/15

Community engagement0/10

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 6d ago via OSV.dev · supermemory-agent (PyPI)

★ Featured

Moxie Docs MCP

MCP & Agent Skills for Automated Documentation, and codebase conventions + context

Explore Server →

Own this project?

Free dofollow backlink: add your website and place the AllMCPs badge on it — no claim needed. We detect it automatically and keep it verified as long as the badge stays live.

Claim & get free dofollow

Share & Embed

Add our SVG badge (dark/light directory styles) or embeddable widget to your site.