Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Local code graph and solution memory for coding agents via CLI and MCP.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"codeagent-memory": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/hanochzhu/codeagent-memory:0.1.6"
]
}
}
}在终端中运行这条命令
claude mcp add codeagent-memory -- docker run -i --rm ghcr.io/hanochzhu/codeagent-memory:0.1.6粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"codeagent-memory": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/hanochzhu/codeagent-memory:0.1.6"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"codeagent-memory": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/hanochzhu/codeagent-memory:0.1.6"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月6日
注册名称已通过 GitHub 账户 HanochZhu 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.1.6)于7天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Docker。
同一分类中有:Context7, Codebase Memory, Exa
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
English · 中文 · 日本語 · 한국어 · العربية · 🌐 Website
Code graph + memory · surgical reads · 100% local · MCP + CLI
Kernel written in Rust
Guides: Interactive Showcase (Website) · Main Agent vs Subagent · MCP Configs by IDE · 中文说明
When an AI coding agent explores a repository, it usually rediscovers structure the slow way — running grep, glob, and full-file Read one file at a time — and forgets everything in the next session.
`cam` gives the agent two local retrieval planes in a single binary:
| Plane | What it stores | How the agent uses it | |
|---|---|---|---|
| Code Graph | Tree-sitter symbols (functions, types, methods) as a virtual filesystem + 1-hop callers/callees | ls, find, read src/file.rs/symbol, `ref symbol --dir in\ | out` — surgical symbol reads instead of whole-file dumps |
| Memory Tree | Project facts, architecture decisions, debugging write-ups, and user habits | recall (Vector + BM25 fused with RRF) and add (with branching --parent and revision --supersedes) |
One binary, two interfaces: The main agent calls
camover MCP (cam mcp); subagents (which rarely inherit MCP tools) call the exact same CLI (cam --json …). Both share.cam/cam.dbon disk, 100% local, zero API cost.
Paste this prompt directly into your coding agent (Cursor, Claude Code, Codex, Windsurf, GitHub Copilot, Cline, etc.) and let it install, index, and wire cam for you:
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.
How each IDE / agent handles this prompt
| Environment | What to do |
|---|---|
| Cursor / Windsurf / Claude Code / Codex | Paste into Agent / Chat; the agent runs the terminal install, builds .cam/cam.db, and writes the MCP config |
| VS Code (Copilot / Continue / Cline) | Paste into Agent / Chat mode with terminal access enabled |
| JetBrains (IntelliJ / RustRover / GoLand) | Paste into AI Assistant, or run cargo install in the built-in terminal |
Note: cargo install places cam in ~/.cargo/bin (Windows: %USERPROFILE%\.cargo\bin). Restart your terminal or IDE if cam is not immediately found on PATH.
Requires a Rust toolchain:
cargo install --git https://github.com/HanochZhu/codeagent_memory --locked
cam --help
Alternative: Build from local clone or run via Docker
From a local clone:
git clone https://github.com/HanochZhu/codeagent_memory.git
cd codeagent_memory cargo install --path . --locked
Docker (no Rust toolchain required):
docker pull ghcr.io/hanochzhu/codeagent-memory:0.1.6
docker run -i --rm -v "$PWD:/work" -w /work ghcr.io/hanochzhu/codeagent-memory:0.1.6
Or build locally: docker build -t cam https://github.com/HanochZhu/codeagent_memory.git
cd your-project
cam index # parse repo into .cam/cam.db
cam ls src/ # list files or symbols in a file cam read src/main.rs/main # read a single symbol body cam ref main --dir in # 1-hop callers (in) or callees (out)
cam recall "how does hybrid recall fuse BM25 and vectors" cam add --summary "..." < notes.md
cam auto-initializes .cam/ on first use. Run cam watch in the background if you want live incremental graph updates as files change.
Add cam mcp to your host's MCP configuration (e.g. .cursor/mcp.json or .mcp.json):
{
"mcpServers": { "cam": { "command": "cam", "args": ["mcp"] } } }
See docs/mcp.md for host-specific config paths and docs/agents.md for main-agent / subagent prompt rules.
The first recall or add downloads the default embedding model (potion-multilingual-128M to ~/.cam/models/) and falls back to a lexical hash embedder if offline.
| Feature | Details |
|---|---|
| SQLite Code Graph | Tree-sitter parses functions, types, and call edges into .cam/cam.db for instant symbol-level navigation |
| Virtual Paths | src/main.rs addresses a file outline; src/main.rs/main addresses the symbol body directly |
| Live Incremental Sync | cam sync hashes file contents; cam watch keeps the graph updated on save |
| Hybrid Recall (RRF) | Combines local dense embeddings (model2vec) + identifier-aware BM25 via Reciprocal Rank Fusion ($k=60$) |
| Revision Chains & Tree | --parent builds branching topic hierarchies; --supersedes links linear revisions and folds older entries automatically |
| Ebbinghaus Retention | Retention $R = e^{-t / S}$ gently weights ranking ($\le 10\%$) and flags stale / needs_update memories without deleting history |
| Dual Interface (MCP + CLI) | Main agent uses cam_* MCP tools; subagents run cam --json … in the shell |
| 100% Local & Private | Zero external API keys; runs entirely on local SQLite and on-disk embeddings |
| 9 Languages | Rust, Python, TypeScript, JavaScript, Go, Java, C, C++, C# |
tree-sitter walks the workspace and stores symbol definitions and call edges in .cam/cam.db.ls → find → read → ref). Reading a file returns its symbol outline; reading file/symbol returns only that symbol's source slice.recall takes an English query, embeds it locally, runs identifier-aware BM25 (splitting snake_case, kebab-case, camelCase + English stemming), prunes low-confidence tails, and fuses both lists with RRF ($k=60$) scaled by $0.9 + 0.1 \times R$. Superseded revisions are automatically expanded to their newest replacement.add stores only one fact (English summary; body supports non-Latin characters). Related facts are connected via --link / links into a knowledge graph (inspected via mem show; recall does not traverse graph links yet). --parent attaches a memory to a structural topic; --supersedes replaces an outdated memory while preserving lineage.Architecture deep dive (Chinese): DESIGN.md.
Every coding task follows the same four-step loop:
cam_recall / cam recall in English before grepping. Reuse a hit if it is latest and not needs_update.not_indexed, run cam_index / cam index once for the project.find or ls, read symbol bodies with read / , and trace callers/callees with ref --dir in|out.cam_add / cam add as atomic facts (one fact per memory, English summary; body supports non-Latin characters), linking related facts with links / --link.| Role | Interface | Typical Usage |
|---|---|---|
| Main Agent (Chat / IDE session) | MCP (cam mcp) | Calls cam_recall, cam_find, cam_ls, cam_read, cam_ref, cam_add, cam_mem_tree, cam_mem_show directly |
| Subagent (Task / explore / CLI) | CLI (cam --json) | Runs cam --json --project in the shell (subagents rarely inherit MCP tools) |
Full agent rules & copy-paste system prompts: docs/agents.md.
| Command | Description | |
|---|---|---|
cam index | Parse the project with tree-sitter into .cam/cam.db (creates .cam/ if needed) | |
cam sync | Incrementally update the graph for modified files using content hashes | |
cam watch [--debounce-ms N] | Watch source files and auto-sync (--json streams one JSON report per sync) | |
cam ls [virt_path] | List directories, files, or symbols inside a file | |
cam read [--full] | Read a file's symbol outline, a specific symbol body (path/symbol), or the --full file | |
cam find [--kind K] [--file S] [--scope D] [--limit N] | Case-insensitive substring search over symbol names (exact matches first, then prefixes) | |
| `cam ref --dir in\ | out [--file S] [--kind K] [--scope D]` | 1-hop callers (in / --callers) or callees (out / --callees). Returns ranked candidates on ambiguous names |
| Command | Description |
|---|
| cam recall " " [--limit N] [--no-expand] [--include-superseded] [--snippets] | Hybrid RRF recall (English query). --no-expand skips newest-revision expansion; --include-superseded keeps old revis
只显示了开头部分;其余内容请在仓库中阅读