Context7
Up-to-date docs for AI agents
作者提供的说明(英文原文)
Semantic code retrieval engine with hybrid search, context expansion, and 40+ language support.
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": {
"contextweaver": {
"command": "npx",
"args": [
"-y",
"@chiway/contextweaver"
]
}
}
}在终端中运行这条命令
claude mcp add contextweaver -- npx -y @chiway/contextweaver粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"contextweaver": {
"command": "npx",
"args": [
"-y",
"@chiway/contextweaver"
]
}
}
}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": {
"contextweaver": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@chiway/contextweaver"
]
}
}
}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 wchiway 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(1.5.4)于5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: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。
🧵 A codebase context engine woven for AI agents
Semantic Code Retrieval for AI Agents — Hybrid Search • Graph Expansion • Token-Aware Packing
English · 简体中文
ContextWeaver is a semantic retrieval engine purpose-built for AI coding assistants. It combines hybrid search (vector + lexical), intelligent context expansion, and token-aware packing to deliver precise, relevant, and context-complete code snippets to LLMs.
displayCode for presentation, vectorText for embeddingSourceAdapter.toCharOffset before writing metadata, preventing multi-byte character slicing errors (v1.4.0+)normalized query + projectId + index version + search-config fingerprint, so it invalidates automatically after an index update or config change — stale results are never returnedcontextweaver watch watches the filesystem and triggers incremental indexing automatically, with debouncing (500ms by default) and scan de-duplication (no concurrent scans)contextweaver stats CLI (with --json) plus the MCP stats toolpending_marks backlog, missing vector rows, and more — with suggested fixesfiles.content, reducing index size by 30–50%pending/done/aborted persisted, auto-rebuilt on crash recovery# Global install
npm install -g @chiway/contextweaver
pnpm add -g @chiway/contextweaver
# Create the config file (~/.contextweaver/.env)
contextweaver init
cw init
Edit ~/.contextweaver/.env and fill in your API keys:
# Embedding API config (required)
EMBEDDINGS_API_KEY=your-api-key-here EMBEDDINGS_BASE_URL=https://api.siliconflow.cn/v1/embeddings EMBEDDINGS_MODEL=BAAI/bge-m3 EMBEDDINGS_MAX_CONCURRENCY=10 EMBEDDINGS_DIMENSIONS=1024
RERANK_API_KEY=your-api-key-here RERANK_BASE_URL=https://api.siliconflow.cn/v1/rerank RERANK_MODEL=BAAI/bge-reranker-v2-m3 RERANK_TOP_N=20
CW_SEARCH_WVEC=0.6 CW_SEARCH_WLEX=0.4 CW_SEARCH_RERANK_TOP_N=10 CW_SEARCH_MAX_TOTAL_CHARS=48000 CW_SEARCH_VECTOR_TOP_K=80 CW_SEARCH_SMART_MAX_K=8 CW_SEARCH_IMPORT_FILES_PER_SEED=3
# Run from the codebase root
contextweaver index
contextweaver index /path/to/your/project
contextweaver index --force
# Watch for file changes and auto-index incrementally (Ctrl+C to stop)
contextweaver watch
contextweaver watch /path/to/project --debounce 800
watch runs one full incremental scan on startup, then listens to filesystem events; changes trigger a de-duplicated scan within the debounce window, and paths excluded by ignore rules never trigger a scan.
# Semantic search
cw search --information-request "How is the user authentication flow implemented?"
cw search --information-request "Database connection logic" --technical-terms "DatabasePool,Connection"
The following commands are CLI mirrors of MCP tools, with zero Embedding API cost:
# List indexed files (supports glob / language / count filters)
contextweaver list-files --glob "src/**/*.ts" --language typescript --max-results 100
contextweaver definition SearchService --hint-path src/search
contextweaver references handleStats --exclude-definition
# Human-readable stats report
contextweaver stats
contextweaver stats --json
contextweaver stats --path /path/to/project
# Launch the MCP server (for use by Claude and other AI assistants)
contextweaver mcp
# Show LanceDB migration state
contextweaver migrate
contextweaver migrate --reset
contextweaver migrate --path /path/to/project
Add the following to your Claude Desktop config file:
{
"mcpServers": { "contextweaver": { "command": "contextweaver", "args": ["mcp"] } } }
ContextWeaver exposes 5 MCP tools, following a layered design of "semantic retrieval first, structure browsing second":
| Tool | Purpose | Embedding cost |
|---|---|---|
codebase-retrieval | Primary tool: hybrid semantic + exact-match retrieval | Yes |
list-files | List indexed file structure (path/language/size) | No |
find-references | Find heuristic text references to a symbol | No |
get-symbol-definition | Find likely definition blocks for a symbol | No |
stats | Index/search/health statistics | No |
codebase-retrieval Parameters| Parameter | Type | Required | Description |
|---|---|---|---|
repo_path | string | ✅ | Absolute path to the repository root |
information_request | string | ✅ | The semantic intent in natural language |
technical_terms | string[] | ❌ | Exact technical terms (class/function names, etc.) |
mode | string | ❌ | Retrieval profile: quick, balanced, or deep |
include_globs | string[] | ❌ | File glob allowlist applied after retrieval |
exclude_globs | string[] | ❌ | File glob denylist applied after retrieval |
language | string[] | ❌ | Language allowlist applied after retrieval |
max_total_chars | number | ❌ | Per-call output budget in characters |
max_files | number | ❌ | Maximum number of files returned after packing |
max_segments_per_file | number | ❌ | Maximum non-contiguous segments per file |
return_debug | boolean | ❌ | Include debug metadata in structured output |
low_confidence_behavior | string | ❌ | Low-confidence handling: return_top1, return_empty, or return_with_warning |
output_format | string | ❌ | Response format: markdown, json, or both |
list-files Parameters| Parameter | Type | Required | Description |
|---|---|---|---|
repo_path | string | ✅ | Absolute path to the repository root |
glob | string | ❌ | Glob pattern to filter paths |
language | string | ❌ | Language filter (matched against files.language) |
max_results | number | ❌ | Max files to return (default 200) |
find-references Parameters| Parameter | Type | Required | Description |
|---|---|---|---|
repo_path | string | ✅ | Absolute path to the repository root |
symbol | string | ✅ | Exact symbol name |
exclude_definition | boolean | ❌ | Exclude chunks whose breadcrumb tail matches the symbol name |
max_results | number | ❌ | Max references to return (default 50) |
get-symbol-definition Parameters| Parameter | Type | Required | Description |
|---|---|---|---|
repo_path | string | ✅ | Absolute path to the repository root |
symbol | string | ✅ | Exact symbol name to resolve |
| hint_path | string | ❌ | Preferred
只显示了开头部分;其余内容请在仓库中阅读