The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Total Agent Memory
Persistent local memory for AI coding agents — Claude Code, Codex CLI, Cursor, any MCP client. Temporal knowledge graph, procedural memory, AST codebase ingest, cross-project…
Install
claude mcp add memory -- total-agent-memoryInstall command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →Persistent, local memory for AI coding agents: Claude Code, Codex CLI, Cursor and any MCP client.
Website and documentation: totalmemory.dev · Quick start · Claude Code guide · Benchmarks · Compare with other tools
total-agent-memory (TAM) is an open-source memory server for AI coding agents. Coding agents start every session without memory of earlier ones, so decisions, fixes and project conventions have to be explained again. TAM stores decisions, solutions, facts, errors and session summaries on your machine and returns them through the Model Context Protocol (MCP), so any MCP client can use it without code changes.
Each store is one directory built around a SQLite database. Recall combines
full-text BM25, dense embeddings computed locally, fuzzy matching and a
knowledge graph, and fuses the ranked lists with reciprocal rank fusion; an
optional cross-encoder can rerank the result. The default profile makes no LLM
call on write or search, so retrieval can be measured offline and a rerun gives
the same result. Facts can carry validity intervals (kg_add_fact, kg_at),
and a newer value of a single-valued fact can retire the older one.
TAM is for developers who use coding agents daily and for researchers who need a memory baseline they can run locally, inspect and change. The same package can also run as a team server: personal, department and company areas are separate stores behind one gateway, with roles, authorship and an audit trail (team server).
Installation
TAM needs Python 3.11 or newer. CI tests Python 3.11, 3.12 and 3.13 on Ubuntu, Windows and macOS.
From PyPI (use a virtual environment, or pipx / uvx):
pip install total-agent-memory # or: pipx install total-agent-memory
uvx total-agent-memory # run once without installing
This installs the total-agent-memory (alias tam) MCP server and the
tam-team, tam-remote and lookup-memory commands. The optional
cross-encoder reranker pulls in PyTorch and is an extra:
pip install "total-agent-memory[rerank]". The PostgreSQL backend of the team
server is the [postgres] extra.
Register it with your clients. Run tam setup at a terminal. The wizard
asks "Just me" or "Company server", detects Claude Code, Claude Desktop, Codex,
Cursor, Windsurf, Gemini CLI, Cline and OpenCode, and registers the server with
the ones you pick (setup wizard).
Other channels:
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