AI Skill Hub 推荐使用:神经智脑知识系统 是一款优质的MCP工具。AI 综合评分 7.2 分,在同类工具中表现稳健。如果你正在寻找可靠的MCP工具解决方案,这是一个值得深入了解的选择。
神经智脑知识系统 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
神经智脑知识系统 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/dfrostar/neuralmind
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"--------": {
"command": "npx",
"args": ["-y", "neuralmind"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 神经智脑知识系统 执行以下任务... Claude: [自动调用 神经智脑知识系统 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"________": {
"command": "npx",
"args": ["-y", "neuralmind"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
Semantic code intelligence for AI coding agents — smart context retrieval + tool-output compression in one package.
NeuralMind turns a code repository into a queryable neural index. AI agents use it to answer code questions in ~800 tokens instead of loading 50,000+ tokens of raw source.
🆕 New in v0.9.0 — Enterprise-Ready. GHCR auto-built multi-platform container image (docker pull ghcr.io/dfrostar/neuralmind:latest), CycloneDX SBOM attached to every release, air-gapped install walkthrough, and a compliance one-pager consolidating NIST AI RMF + SOC 2 + GDPR claims. Release notes v0.8.0 — Always-On.neuralmind watch+neuralmind serverun as first-class services with committed systemd + launchd templates + a Windows Task Scheduler walkthrough in the Scheduling Guide + a/healthzendpoint for Docker HEALTHCHECK and systemd ExecStartPost probes. Release notes v0.7.0 — Install anywhere. Five install paths now in the README:pip,pipx,uv, Docker, and source. Same package every path; smoke-test verified. Release notes · Install matrix ↓ v0.6.0 — Obsidian-style graph view with a live activity feed.neuralmind servestreams synapse + file events to the canvas in real time, so you can watch the brain learning your codebase. Release notes · Graph view section ↓
🌐 Visit the landing page • 📖 Read the About page • ⚖️ Not affiliated with NeuralMind.ai
---
neuralmind serve ships in v0.5.4 — see the Graph view section above. The next patch release (v0.5.5) lands graph-view Phase B: the replay-last-query overlay (#105), edge tooltips + min-weight synapse slider (#106), pin UX, and a Cmd/Ctrl-K quick-switch. Phase C after that: a live activity feed of synapse co-activations. Full plan in ROADMAP.md.
NeuralMind now runs as a second brain alongside the LLM: a persistent associative memory that learns continuously from how the agent and the codebase actually interact. See the release notes for the full story.
| Feature | Details |
|---|---|
| **Synapse store** | SQLite-backed weighted graph; Hebbian reinforce, decay, long-term potentiation |
| **Spreading activation** | mind.synaptic_neighbors(query) — usage-based recall complementing vector search |
**neuralmind watch daemon** | File edits become co-activation signals; brain learns even when no query runs |
| **Three new Claude Code hooks** | SessionStart (decay+export), UserPromptSubmit (recall injection), PreCompact (hub normalization) |
| **Auto-memory export** | Writes SYNAPSE_MEMORY.md to Claude Code's auto-memory dir so associations surface natively |
| **Three new MCP tools** | synaptic_neighbors, synapse_stats, synapse_decay, export_synapse_memory |
| **3× fewer embedder calls per query** | Selector caches one search per query and slices for L2/L3/synapses |
graphify update .
NeuralMind installs five ways. The CLI, semantic indexing, and the MCP server (for Claude Code, Cursor, Cline, Continue, and any MCP client) come in every path.
| Method | Command | When to pick |
|---|---|---|
| **pip** | pip install neuralmind graphifyy | Default. Drops it in your active env. |
| **pipx** | pipx install neuralmind && pipx inject neuralmind graphifyy | Global CLI, no env pollution. Recommended if you want neuralmind available everywhere. |
| **uv** | uv pip install neuralmind graphifyy | Modern, fast Python tooling. ~10× faster install than pip. |
| **Docker** | docker pull ghcr.io/dfrostar/neuralmind:latest && docker run --rm -v "$PWD:/project:ro" ghcr.io/dfrostar/neuralmind:latest neuralmind --help | Containerized — no Python on the host. Multi-platform (linux/amd64 + linux/arm64); auto-published to GHCR on every release since v0.9.0. To build locally instead: docker build -t neuralmind:dev . and substitute that tag. |
| **From source** | git clone … && pip install -e . | Hacking on NeuralMind itself. |
Verify install:
```bash neuralmind --help # works for every install path
python -c "import neuralmind; print(neuralmind.version)" ```
The python -c line is skipped for pipx and Docker — pipx isolates the package in its own venv, and Docker doesn't expose the in-container Python.
Walkthrough with pros/cons of each path: docs/use-cases/install-paths.md.
neuralmind build .
neuralmind install-hooks .
neuralmind init-hook .
Build or incrementally update the neural index from graphify-out/graph.json.
neuralmind build [project_path] [--force]
| Argument/Option | Default | Description |
|---|---|---|
project_path | . | Project root containing graphify-out/graph.json |
--force, -f | off | Re-embed every node even if unchanged |
neuralmind build .
neuralmind build /path/to/project --force
Output: nodes processed, added, updated, skipped, communities indexed, build duration.
---
Install or remove Claude Code PostToolUse compression hooks.
neuralmind install-hooks [project_path] [--global] [--uninstall]
| Option | Description |
|---|---|
--global | Install in ~/.claude/settings.json (affects all projects) |
--uninstall | Remove NeuralMind hooks only; preserves other tools' hooks |
neuralmind install-hooks . # project-scoped
neuralmind install-hooks --global # all projects
neuralmind install-hooks --uninstall # remove project hooks
neuralmind install-hooks --uninstall --global # remove global hooks
---
<details> <summary><b>Claude Code</b> — full two-phase optimization</summary>
pip install neuralmind graphifyy
cd your-project
graphify update .
neuralmind build .
neuralmind install-hooks . # PostToolUse compression
neuralmind init-hook . # auto-rebuild on commit (optional)
Then use MCP tools in sessions: neuralmind_wakeup, neuralmind_query, neuralmind_skeleton. </details>
<details> <summary><b>Cursor / Cline / Continue</b> — MCP server</summary>
pip install neuralmind graphifyy
graphify update .
neuralmind build .
Add to your MCP config:
{ "mcpServers": { "neuralmind": { "command": "neuralmind-mcp" } } } </details>
<details> <summary><b>ChatGPT / Gemini / any LLM</b> — CLI + copy-paste</summary>
neuralmind wakeup . | pbcopy # macOS — paste into chat
neuralmind query . "question" # get context for a specific question </details>
---
{
"mcpServers": {
"neuralmind": {
"command": "neuralmind-mcp",
"args": ["/absolute/path/to/project"]
}
}
}
Config file locations:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json~/.config/Claude/claude_desktop_config.json| Tool | When to call | Required params | Returns |
|---|---|---|---|
neuralmind_wakeup | Session start | project_path | L0+L1 context string, token count |
neuralmind_query | Code question | project_path, question | L0–L3 context string, token count, reduction ratio |
neuralmind_search | Find entity | project_path, query | List of nodes with scores, file paths |
neuralmind_skeleton | Explore file | project_path, file_path | Functions + rationales + call graph + cross-file edges |
neuralmind_recursive_query | Complex question | project_path, question | Synthesized answer, sub-queries, gaps, sources |
neuralmind_query_docs | Reference docs | project_path, question | Relevant doc chunks with source files and relevance scores |
neuralmind_stats | Check status | project_path | Built status, node count, community count |
neuralmind_build | Rebuild index | project_path | Build stats dict |
neuralmind_benchmark | Measure savings | project_path | Per-query token counts and reduction ratios |
---
Every new session, do this first:
neuralmind wakeup .
Or via MCP:
neuralmind_wakeup(project_path=".")
This returns ~365–600 tokens of structured project context:
CLAUDE.md, mempalace.yaml, or README.md first line)graphify-out/GRAPH_REPORT.md if presentUse this output as your orientation before writing any code. It replaces reading the entire repository.
---
Short answers to "why not just use X?". Each row links to a deeper page.
| Compared against | Short verdict |
|---|---|
[Cursor @codebase](docs/comparisons/vs-cursor-codebase.md) | Works *only* in Cursor; NeuralMind works in any agent and adds tool-output compression |
| [Aider repo-map](docs/comparisons/vs-aider-repomap.md) | Aider is syntactic only; NeuralMind adds semantic retrieval and compression |
| [Sourcegraph Cody](docs/comparisons/vs-cody.md) | Cody is server-hosted and org-wide; NeuralMind is local and per-project |
| [Continue / Cline](docs/comparisons/vs-continue-cline.md) | Those are agent runtimes; NeuralMind is the context/compression layer underneath |
| [GitHub Copilot](docs/comparisons/vs-github-copilot.md) | Copilot is hosted completions; NeuralMind is local context for any agent |
| [Windsurf / Codeium](docs/comparisons/vs-windsurf-codeium.md) | Vertically integrated IDE; NeuralMind is editor- and model-agnostic |
| [Claude Projects](docs/comparisons/vs-claude-projects.md) | Projects reload all files every turn; NeuralMind retrieves only what the query needs |
| [Prompt caching](docs/comparisons/vs-prompt-caching.md) | Caching amortizes a big prompt; NeuralMind makes the prompt small — combine both |
| [LangChain / LlamaIndex for code](docs/comparisons/vs-langchain-llamaindex.md) | Frameworks you assemble; NeuralMind is the assembled default for code agents |
| [Long context windows (1M/2M)](docs/comparisons/vs-long-context.md) | Possible ≠ cheap — NeuralMind gives ~60× cost reduction on the same model |
| [Generic RAG over a codebase](docs/comparisons/vs-rag.md) | Text chunking loses structure; NeuralMind keeps the call graph |
| [Tree-sitter / ctags / grep](docs/comparisons/vs-treesitter-ctags.md) | Deterministic but syntactic; use alongside NeuralMind, not instead of |
Full comparison index: docs/comparisons/.
---
"Connection closed" / "Connection failed" right after register. Almost always means an old NeuralMind install (≤ 0.4.x) where the MCP server was gated behind the [mcp] extra. From 0.5.0 onward the MCP SDK is bundled. Fix:
pip install --upgrade neuralmind
Then re-run the host's verify step (hermes mcp test neuralmind or openclaw mcp list).
neuralmind-mcp: command not found. The package installed but the console script wasn't put on PATH — usually because pip installed into a user site-packages dir that isn't on PATH. Add ~/.local/bin to PATH or reinstall in a venv where the entry point is on PATH.
The host shows neuralmind in mcp list but no tools when you query. Run neuralmind build /path/to/project first — the index has to exist before the MCP tools can answer queries. The hooks (SessionStart, UserPromptSubmit, PreCompact from neuralmind install-hooks) need a built index too.
🧠 NeuralMind 项目简介
✨ NeuralMind 的新功能介绍(v0.5.4 和 v0.4.0 的更新)
环境依赖与系统要求中文说明(包括 graphify 的生成)
📦 NeuralMind 的安装步骤说明(包括 Docker、pip 和源码等部署方式)
🚀 NeuralMind 的使用教程(包括快速启动和 CLI 参考)
配置说明(包括 MCP 服务器、环境变量和关键参数)
MCP 工具快速参考(包括 neuralmind_wakeup、neuralmind_query 等)
每个新会话的启动工作流程(包括 neuralmind_wakeup 等命令)
❓ NeuralMind 常见问题解答
创新的token优化方案,利用向量检索和神经网络降低上下文成本。但项目热度低,生产适用性有待验证,适合研究探索。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
总体来看,神经智脑知识系统 是一款质量良好的MCP工具,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | neuralmind |
| 原始描述 | 开源MCP工具:🧠 Adaptive Neural Knowledge System - 40-70x token reduction for AI code underst。⭐8 · Python |
| Topics | 代码理解token优化向量数据库上下文管理神经网络 |
| GitHub | https://github.com/dfrostar/neuralmind |
| License | MIT |
| 语言 | Python |
收录时间:2026-05-18 · 更新时间:2026-05-24 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端