codeagent-memory MCP server

cam

English · 中文

A local multi-turn conversational memory system purpose-built for coding agents

Code graph + memory · surgical reads · 100% local · MCP + CLI

Kernel written in Rust

Contents

• Why cam?
• Get Started
• Benchmarks
• Key Features
• How It Works
• Agent Workflow
• CLI Reference
• Memory Rules
• Configuration
• Supported Platforms
• Supported Agents
• Supported Languages

Usage details: main agent vs subagent · MCP configs for each IDE · 中文说明

Why cam?

When an AI agent needs to understand code — or reuse what it already learned about this project — it discovers structure the slow way: grep, glob, and Read, one file at a time. Next session it does the same work again.

cam hands the agent two things it can query in one shell call:

1. A code graph — every indexed file and symbol as a virtual filesystem, plus one-hop callers / callees.
2. A memory tree — habits, project facts, designs, write-ups; recalled with vector + BM25 so the agent does not re-learn the same project.

Surgical reads, not a file-by-file search. Memories stay on disk, 100% local.

One binary, two doors: the main agent uses MCP (cam mcp); subagents usually have no MCP, so they run the same CLI. Configs: docs/mcp.md. Usage: docs/agents.md.

Get Started

1. Install the CLI

Need Rust first? Install it from rustup.rs, then:

cargo install --git https://github.com/HanochZhu/codeagent_memory --locked
cam --help

Paste this into an AI instead (Cursor, Claude Code, Copilot, …)

Install cam from https://github.com/HanochZhu/codeagent_memory: require a working Rust toolchain (rustup), run `cargo install --git https://github.com/HanochZhu/codeagent_memory --locked`, ensure ~/.cargo/bin (or %USERPROFILE%\.cargo\bin on Windows) is on PATH, then verify with `cam --help`. In this repo run `cam index`. For the main agent, register MCP stdio: command `cam`, args `["mcp"]` (Cursor: .cursor/mcp.json; Claude Code: .mcp.json). Subagents call `cam --json` in the shell. Do not add extra docs.

Shortened. The full README is on GitHub.