AgentToolDrop

3 of 43

agent-memory

Gives coding agents a shared long-term memory kept as plain Markdown files, with local ranked recall

Install from a checkout with uv

git clone https://github.com/tigerless-labs/agent-memory.git
cd agent-memory
uv sync --all-packages

Copied from the project's docs at github.com/tigerless-labs/agent-memory

Why you'd want it

agent-memory keeps each memory as one Markdown file in a single store, with a SQLite index beside it that can be deleted and rebuilt at any time. Recall runs locally and returns a ranked list of paths with one-line abstracts, so the agent opens only what it needs, and Claude Code, Codex CLI and Muse Code can share the same store. Hooks write memories at conversation boundaries, and a separate sleep-time pass consolidates them, with deletions only arriving as proposals you confirm. It needs no API key of its own and borrows judgement from the host agent's CLI.

Best for

  • Memory shared between Claude Code and Codex
  • Memory you can grep and keep in git
  • Agents that forget between sessions

Use it when

You want an agent to remember decisions across sessions and prefer a store you can read, grep and commit over an opaque database.

Skip it if

You want a packaged install: there is no PyPI release yet, so it installs from a git checkout with uv, and the repo was created on 2026-09-01. Setup writes lifecycle hooks into your agent's settings and runs the host agent's CLI headlessly to distil and consolidate memories.

Editor's note

After installing, mem setup --host claude-code or mem setup --host codex installs the hooks and skill; add --mcp to also register the stdio MCP server.

Related tools

Same category or shared tags.

  1. Rank 25

    Cognee

    Memory

    Turns documents, code and conversations into a knowledge graph that agents store to and recall from

    • score 39
    • 32.3k stars
    • 28 stars/day since creation
    • pushed
    • v1.6.4 on
    • Apache-2.0

    Install with uv

    uv pip install "cognee[gliner]"
    Use it when, skip it if, stats for Cognee

    Why you'd want it

    Cognee ingests text, code and session data and builds connected memory: entities, relationships and searchable chunks for text, and a graph of symbols and dependencies for code. Its API centers on four operations (remember, recall, improve and forget), and with the gliner extra it builds and queries memory with small local CPU models and no API key, while adding an LLM key enables generated answers. It ships plugins for Claude Code and Codex, an MCP server for other clients, a REST API and Docker images for self-hosting.

    Best for

    • Agent memory across runs on your own infrastructure
    • Shared memory over docs, tickets and code
    • Local experiments without an LLM API key

    Use it when

    You want agents to keep and query project knowledge, past decisions and fixes across sessions, on infrastructure you control.

    Skip it if

    You are not on Python 3.10 to 3.14 for the library. Running the whole memory layer on a single Postgres instance is a demo feature; the production version is a licensed product.

    Stats

    Stars
    32,313
    Last push
    Release
    v1.6.4,
    License
    Apache-2.0
    Pricing
    Open source
    Works with
    Claude Code, Codex, Cursor, Any MCP client, Docker
    Stars per day, since repo creation
    28
    New and rising score
    39 of 100

    Full stat block for Cognee

  2. Rank 17

    Graphiti

    Memory

    Builds temporal knowledge graphs from agent conversations and data, tracking how facts change over time

    • score 44
    • 31.8k stars
    • 39.8 stars/day since creation
    • pushed
    • v0.31.0 on
    • Apache-2.0

    Install with pip

    pip install graphiti-core
    Use it when, skip it if, stats for Graphiti

    Why you'd want it

    Graphiti turns episodes (raw text or JSON) into entities and relationships and gives each fact a validity window, so when information changes the old fact is invalidated rather than deleted and you can query what was true at any point. New data is added incrementally without recomputing the graph, and retrieval combines semantic embeddings, BM25 keyword search and graph traversal. Every fact traces back to the episode that produced it, custom entity and edge types are defined with Pydantic models, and a bundled MCP server lets assistants add and search memory.

    Best for

    • Agents working on data that changes over time
    • Memory that needs provenance back to sources
    • Teams comfortable running a graph database

    Use it when

    You need agent memory that answers questions about relationships and history, not just similar text chunks.

    Skip it if

    You do not want to run a graph database: Graphiti needs Neo4j, FalkorDB or Amazon Neptune plus an LLM with structured output, OpenAI by default. Zep is the managed option from the same team, and anonymous telemetry is on by default (opt out with GRAPHITI_TELEMETRY_ENABLED=false).

    Stats

    Stars
    31,759
    Last push
    Release
    v0.31.0,
    License
    Apache-2.0
    Pricing
    Open source
    Works with
    Claude Desktop, Cursor, Any MCP client
    Stars per day, since repo creation
    39.8
    New and rising score
    44 of 100

    Full stat block for Graphiti

  3. Rank 18

    ccusage

    Devtool

    Reports token usage and costs for Claude Code, Codex and other coding agent CLIs from local data

    • score 44
    • 19k stars
    • 37.7 stars/day since creation
    • pushed
    • v20.0.33 on
    • MIT

    Run with npx

    npx ccusage@latest
    Use it when, skip it if, stats for ccusage

    Why you'd want it

    ccusage reads the usage data that coding agent CLIs store locally and turns it into daily, weekly, monthly and session reports, with per-model breakdowns and separate cache token counts. One report covers Claude Code, Codex, OpenCode, Gemini CLI, GitHub Copilot CLI and more than a dozen other tools, and there are Claude Code extras such as 5-hour billing window reports and a status line integration. Output is a table or JSON, and an offline mode uses cached pricing data.

    Best for

    • Tracking spend across several coding agents
    • Claude Code users watching 5-hour usage windows
    • Exporting usage as JSON for your own dashboards

    Use it when

    You want to see how many tokens and dollars your coding agent sessions use, by day, model, session or project.

    Skip it if

    You need team-wide spend tracking: it only reads local data on the machine where it runs. Costs are calculated from LiteLLM pricing data, not read from your provider bill.

    Stats

    Stars
    19,007
    Last push
    Release
    v20.0.33,
    License
    MIT
    Pricing
    Open source
    Works with
    Claude Code, Codex, Gemini CLI
    Stars per day, since repo creation
    37.7
    New and rising score
    44 of 100

    Full stat block for ccusage

For agents

The same entry, as files an agent can read without scraping this page. 

# read one entry
curl -s https://agenttooldrop.com/tools/agent-memory.md

# list the MCP servers in the catalog
curl -s https://agenttooldrop.com/tools.json \
  | jq -r '.tools[] | select(.category=="mcp-server") | .slug'