GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
作者提供的说明(英文原文)
Indexes codebase into a local knowledge graph with 40+ AI tools and codebase-guard.
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": {
"codebase-synapse": {
"command": "npx",
"args": [
"-y",
"codebase-synapse"
]
}
}
}在终端中运行这条命令
claude mcp add codebase-synapse -- npx -y codebase-synapse粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"codebase-synapse": {
"command": "npx",
"args": [
"-y",
"codebase-synapse"
]
}
}
}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": {
"codebase-synapse": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"codebase-synapse"
]
}
}
}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7日
注册名称已通过 GitHub 账户 iwiels 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(0.1.13)于3个月前进入注册中心。
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 Node.js。
同一分类中有:GitHub, Desktop Commander, Cloudflare MCP
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
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
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。
Give your AI agent a deep understanding of your entire codebase.
An MCP server that indexes your codebase into a local knowledge graph with 52 AI tools — semantic search, call-graph traversal, git archaeology, blast-radius analysis, and more.
Works with Claude Code · Cursor · Windsurf · Zed · Any MCP client
AI coding agents (Claude, Cursor, etc.) are powerful — but they work with limited context. They can only see the files you open or feed them. Ask about call chains, architectural patterns, or blast-radius impact, and they guess.
Codebase Synapse fixes this. It indexes your entire repo into a local knowledge graph stored in SQLite, giving your AI agent real answers backed by structural analysis — not hallucinations.
graph LR
A["📁 Your Codebase"] -->|Tree-sitter| B["🧩 Parser"] B -->|Symbols & Edges| C["🕸️ Knowledge Graph"] C -->|SQLite| D["💾 Local DB"] D -->|52 MCP Tools| E["🤖 AI Agent"]
style A fill:#1a1b26,stroke:#7aa2f7,color:#c0caf5 style B fill:#1a1b26,stroke:#bb9af7,color:#c0caf5 style C fill:#1a1b26,stroke:#9ece6a,color:#c0caf5 style D fill:#1a1b26,stroke:#e0af68,color:#c0caf5 style E fill:#1a1b26,stroke:#f7768e,color:#c0caf5
codebase-synapse index /path/to/your/repo
Indexing runs as a separate CLI command and writes into ~/.codebase-synapse/codebase.db. The first index is the slow one; re-running it only re-indexes changed files. The MCP server never indexes — it only reads the pre-built index.
npx codebase-synapse
That's it. No Docker. No database setup. No cloud. The server starts via stdio and serves the pre-built index to your MCP client.
Claude Code / Claude Desktop
Add to your claude_desktop_config.json or mcp_servers.json:
{
"mcpServers": { "codebase-synapse": { "command": "npx", "args": ["-y", "codebase-synapse"] } } }
Cursor
Add to your .cursor/mcp.json:
{
"mcpServers": { "codebase-synapse": { "command": "npx", "args": ["-y", "codebase-synapse"] } } }
Other MCP clients
Any MCP client that supports stdio transport works. Just point it at:
npx -y codebase-synapse
| Tool | Description |
|---|---|
semantic_search | Vector similarity search using local embeddings (all-MiniLM-L6-v2) |
search_code | Full-text search across code (FTS5 + BM25 ranking) |
search_symbol | Find functions, classes, types by name or pattern |
hybrid_search | Combined semantic + lexical search with RRF fusion |
find_similar | Find structurally similar code using MinHash + LSH |
find_symbol_everywhere | Locate a symbol across all indexed projects |
| Tool | Description |
|---|---|
get_callers / get_callees | Navigate the call graph in either direction |
get_imports / get_dependents | Trace dependency chains |
impact_analysis | Compute blast radius before editing a file |
find_path | Find the shortest connection between two symbols |
find_dead_code | Detect unreachable functions and unused exports |
get_pagerank | Identify the most critical nodes in your architecture |
query_graph | Run Cypher-like queries against the knowledge graph |
| Tool | Description |
|---|---|
get_architecture | Full project architecture overview (languages, entry points, hotspots) |
get_file_structure | Directory tree with symbol annotations |
project_overview | High-level summary with key metrics |
get_route_map | Extract HTTP routes and their handler mappings |
suggest_boundaries | Detect module boundaries via Leiden clustering |
check_boundaries | Validate cross-module dependencies against defined boundaries |
get_clusters | Community detection across the codebase |
| Tool | Description |
|---|---|
git_archaeology | Deep history analysis of a file (authors, churn, evolution) |
get_hotspots | Files with highest complexity × change frequency |
detect_change_coupling | Files that always change together |
get_recent_semantic_changes | Semantically meaningful recent changes |
index_git_history | Build temporal analysis from git log |
| Tool | Description |
|---|---|
memory_store / memory_search / memory_list | Persistent notes, facts, and decisions across sessions |
session_remember / session_recall | Short-term memory within a session |
get_context | Budgeted context preparation for AI agents |
get_edit_context | Focused context for a specific file edit |
get_working_set | Recently accessed and modified files |
manage_adr | Architecture Decision Records management |
Included as a bonus: `codebase-guard` is a PreToolUse hook for Claude Code that blocks writes to high-impact files until the agent runs impact_analysis first.
It uses PageRank scores and blast-radius data from the knowledge graph to identify architectural hubs. No more accidental edits to core files.
| Language | Rust (compiled native binary) |
| Transport | MCP stdio (JSON-RPC) |
| Storage | SQLite (WAL mode, zero config) |
| Embeddings | all-MiniLM-L6-v2 via Candle (offline, local, lazy-loaded) |
| Parsing | Tree-sitter (10 languages) |
| Distribution | npm with prebuilt binaries (Windows, macOS, Linux × x64, arm64) |
Rust · Python · TypeScript · JavaScript · Go · Java · C# · PHP · C · C++
src/
├── parser/ # Tree-sitter parsing & entity extraction ├── graph/ # Knowledge graph, PageRank, Leiden clustering ├── indexer/ # Repository indexing pipeline ├── search/ # BM25 full-text + vector cosine + hybrid RRF ├── embedding/ # Candle-based local embeddings (feature-gated) ├── memory/ # Persistent & session memory stores ├── mcp/ # MCP protocol transport + 52 tool handlers ├── git/ # Git archaeology, intent classification, hotspots ├── context/ # Budgeted context preparation for AI ├── cypher/ # Nom-based Cypher parser → SQL CTE planner ├── similarity/ # MinHash + LSH structural similarity ├── semantic/ # Multi-signal scoring (tokens, directory, AST) └── cli/ # Interactive TUI installer + artifact export/import
Contributions are welcome! The project uses standard Rust tooling:
# Run tests
cargo test
cargo clippy -- -D warnings
cargo fmt --all
Apache-2.0