原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Contextweaver

作者:wchiway版本 1.5.4i★ –i在你的电脑上运行
注册名称io.github.wchiway/contextweaver

安装

概览

作者提供的说明(英文原文)

Semantic code retrieval engine with hybrid search, context expansion, and 40+ language support.

PopNx MCP 的三大支柱

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。

它能帮你做什么

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。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 搜索与 AI 记忆

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • npm已安装 Node.js(用于 npx 命令)

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

在 Cursor 中打开

或者自己复制设置

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。

在 VS Code 中打开

或者自己复制设置

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。

它能做什么

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。

基础检查i

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

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 wchiway 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    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“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 7246 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7246 个服务器的 16% 更新
  • 基础检查结果等于或优于此分类中其他 7246 个服务器的 100%

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。

常见问题

Contextweaver 安全吗?

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。

它需要哪些密钥或代码?

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。

它在我的电脑上运行还是在云端?

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)。

它还在维护吗?

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。

哪些应用可以使用它?

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。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

替代选择

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

Context7

作者:upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT今天更新
安装

Codebase Memory

作者:DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT20天前更新
安装

Exa

作者:exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT上个月更新
安装

作者的 README

打开 README

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。

ContextWeaver

🧵 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.

✨ Core Features

🔍 Hybrid Retrieval Engine
  • Vector Retrieval: deep semantic understanding via similarity
  • Lexical Retrieval (FTS): exact matching for function names, class names, and other technical terms
  • RRF Fusion (Reciprocal Rank Fusion): intelligently merges multiple recall channels
🧠 AST Semantic Chunking
  • Tree-sitter parsing: supports TypeScript, JavaScript, Python, Go, Java, Rust, C, C++, C#, and more
  • Dual-Text strategy: displayCode for presentation, vectorText for embedding
  • Gap-Aware merging: handles code gaps intelligently while preserving semantic integrity
  • Breadcrumb injection: vector text carries hierarchical paths to boost recall
  • UTF-16 character-domain normalization: offsets are unified via SourceAdapter.toCharOffset before writing metadata, preventing multi-byte character slicing errors (v1.4.0+)
📊 Three-Stage Context Expansion
  • E1 Neighbor expansion: adjacent chunks within the same file, preserving block completeness
  • E2 Breadcrumb completion: sibling methods under the same class/function for structural understanding
  • E3 Import resolution: cross-file dependency tracking (configurable toggle)
🎯 Smart TopK Cutoff
  • Anchor & Floor: dynamic threshold plus an absolute floor as dual safeguards
  • Delta Guard: prevents misjudgment in Top1-outlier scenarios
  • Safe Harbor: the first N results only check the floor, guaranteeing baseline recall
🔌 Native MCP Support
  • MCP Server mode: launch a Model Context Protocol server with one command
  • Multi-tool granularity (v1.5.0+): beyond core semantic retrieval, adds dedicated tools for structure browsing, symbol references, symbol definitions, and statistics
  • Intent/term separation: an LLM-friendly API design
  • Auto-indexing: the first query triggers indexing automatically; incremental updates are transparent
⚡ Query Cache & File Watching (v1.5.0+)
  • Query cache (QueryCache): in-process per-project LRU cache (50 entries by default); a hit skips the entire vector recall / rerank / expansion pipeline
  • Automatic cache invalidation: the cache key is composed of normalized query + projectId + index version + search-config fingerprint, so it invalidates automatically after an index update or config change — stale results are never returned
  • Watch mode: contextweaver watch watches the filesystem and triggers incremental indexing automatically, with debouncing (500ms by default) and scan de-duplication (no concurrent scans)
📈 Statistics & Observability (v1.5.0+)
  • Three metric groups: indexing process, search quality/behavior, health/consistency
  • Dual exits: contextweaver stats CLI (with --json) plus the MCP stats tool
  • Consistency diagnostics: automatically detects abnormal migration state, pending_marks backlog, missing vector rows, and more — with suggested fixes
🛡️ Crash-Safe Data Architecture (v1.4.0+)
  • Single source of truth for content: LanceDB stores only vectors and locating metadata; content is read back from files.content, reducing index size by 30–50%
  • Cross-store transactional compensation: three-stage write LanceDB → FTS+outbox → SQLite mark, with automatic rollback or replay on any failure
  • Migration state machine: pending/done/aborted persisted, auto-rebuilt on crash recovery
  • Cross-process mutual exclusion: an advisory lock prevents the MCP server and CLI from triggering LanceDB migration concurrently
  • chunk_id de-duplication: pre-delete before write to avoid duplicate rows on retry

📦 Quick Start

Requirements
  • Node.js >= 20
  • pnpm (recommended) or npm
Installation
# Global install

npm install -g @chiway/contextweaver

Or with pnpm

pnpm add -g @chiway/contextweaver

Initialize Configuration
# Create the config file (~/.contextweaver/.env)

contextweaver init

Or the short alias

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

Reranker config (required)

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

Search parameters (optional, override built-in defaults)

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

Ignore patterns (optional, comma-separated)

IGNORE_PATTERNS=.venv,node_modules

Index a Codebase
# Run from the codebase root

contextweaver index

Specify a path

contextweaver index /path/to/your/project

Force a full re-index

contextweaver index --force

Watch Mode (v1.5.0+)
# Watch for file changes and auto-index incrementally (Ctrl+C to stop)

contextweaver watch

Specify a path and debounce window (ms)

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.

Local Search
# Semantic search

cw search --information-request "How is the user authentication flow implemented?"

With exact terms

cw search --information-request "Database connection logic" --technical-terms "DatabasePool,Connection"

Structure Browsing & Symbol Lookup (v1.5.0+)

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

Look up a symbol definition

contextweaver definition SearchService --hint-path src/search

Look up symbol references

contextweaver references handleStats --exclude-definition

Statistics (v1.5.0+)
# Human-readable stats report

contextweaver stats

JSON output (for scripting)

contextweaver stats --json

Specify a project path

contextweaver stats --path /path/to/project

Start the MCP Server
# Launch the MCP server (for use by Claude and other AI assistants)

contextweaver mcp

Index Management (v1.4.0+)
# Show LanceDB migration state

contextweaver migrate

Clear the aborted state: wipe LanceDB and trigger a full rebuild

Triggered when: the Indexer refuses to write after sampling validation fails;

run this, then index again.

contextweaver migrate --reset

Specify a project path

contextweaver migrate --path /path/to/project

🔧 MCP Integration

Claude Desktop Configuration

Add the following to your Claude Desktop config file:

{

"mcpServers": { "contextweaver": { "command": "contextweaver", "args": ["mcp"] } } }

MCP Tools Overview (v1.5.0+)

ContextWeaver exposes 5 MCP tools, following a layered design of "semantic retrieval first, structure browsing second":

ToolPurposeEmbedding cost
codebase-retrievalPrimary tool: hybrid semantic + exact-match retrievalYes
list-filesList indexed file structure (path/language/size)No
find-referencesFind heuristic text references to a symbolNo
get-symbol-definitionFind likely definition blocks for a symbolNo
statsIndex/search/health statisticsNo
codebase-retrieval Parameters
ParameterTypeRequiredDescription
repo_pathstring✅Absolute path to the repository root
information_requeststring✅The semantic intent in natural language
technical_termsstring[]❌Exact technical terms (class/function names, etc.)
modestring❌Retrieval profile: quick, balanced, or deep
include_globsstring[]❌File glob allowlist applied after retrieval
exclude_globsstring[]❌File glob denylist applied after retrieval
languagestring[]❌Language allowlist applied after retrieval
max_total_charsnumber❌Per-call output budget in characters
max_filesnumber❌Maximum number of files returned after packing
max_segments_per_filenumber❌Maximum non-contiguous segments per file
return_debugboolean❌Include debug metadata in structured output
low_confidence_behaviorstring❌Low-confidence handling: return_top1, return_empty, or return_with_warning
output_formatstring❌Response format: markdown, json, or both
list-files Parameters
ParameterTypeRequiredDescription
repo_pathstring✅Absolute path to the repository root
globstring❌Glob pattern to filter paths
languagestring❌Language filter (matched against files.language)
max_resultsnumber❌Max files to return (default 200)
find-references Parameters
ParameterTypeRequiredDescription
repo_pathstring✅Absolute path to the repository root
symbolstring✅Exact symbol name
exclude_definitionboolean❌Exclude chunks whose breadcrumb tail matches the symbol name
max_resultsnumber❌Max references to return (default 50)
get-symbol-definition Parameters
ParameterTypeRequiredDescription
repo_pathstring✅Absolute path to the repository root
symbolstring✅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

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