Meeba Brain

io.github.meemoprasad由 GitHub 账号 meemoprasad 发布v1.0.1更新于 Oct 24, 2026

Repository knowledge graph MCP server for codebase understanding and debugging.

发布方自己的服务:BrainDog

已验证Streamable HTTP可网页运行知识与记忆开发者工具

概览

AI 生成的概览

一个远程 MCP 服务器,为 AI 助手提供已索引代码库的结构化上下文:符号、调用方、被调用方和依赖关系。

可以做什么
用语义加关键词的混合搜索在已索引代码库中检索,回答开放式代码问题。查询函数、类或方法的定义位置,含文件、行范围和签名元数据。基于解析出的调用图列出某函数的全部调用方,以及它调用的全部函数。查看某个文件导入了什么、依赖什么。
适用场景
适合在不熟悉的代码库中工作、调试跨多个文件或服务的代码,或在重命名函数、修改签名、重构文件之前评估影响范围。
运行要求
远程 HTTP 端点。需要 Meeba Brain 账号,在 Meeba Brain 上连接并完成索引的代码库,并在该平台启用 MCP 以获取密钥。密钥通过客户端配置中的认证请求头提供。
安装前请注意
README 要求妥善保管 Meeba Brain MCP 密钥,它是访问你已索引代码库的凭据。服务器读取的是已上传并索引到 Meeba Brain 云服务的代码内容,因此代码会离开本机。它只提供只读的结构化上下文,不会修改代码。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Meeba Brain,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.meemoprasad%2Fmeeba-brain/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "mcpServers": {
    "meeba-brain": {
      "type": "http",
      "url": "https://meeba-context-mcp-469248886325.us-central1.run.app/mcp"
    }
  }
}

README

Meeba Brain MCP

Repository Knowledge Graph for Cursor

Give your AI coding assistant a structural understanding of your codebase.

Meeba Brain MCP connects Cursor to Meeba Brain's repository knowledge graph, helping it understand how functions, files, services, and dependencies are connected.

Instead of relying only on text search, Cursor can use Meeba Brain's structural context to investigate unfamiliar code, trace relationships, and reason about changes with better grounding.

Why Meeba Brain?

Text search helps you find where a name or phrase appears.

A knowledge graph helps you understand how the code is connected.

For example, instead of only finding refundOrder, you can investigate:

  • Which services call this function?
  • What does this function call?
  • How does this API connect to the underlying implementation?
  • Which parts of the codebase may be affected by this change?

The difference is not simply finding more text. It is understanding the relationships between the code.

How does this help with the correct fix?

When debugging, the file showing the error is not always the file causing the problem.

A bug may involve several connected components:

API route → service → worker → dependency

Without understanding those relationships, an AI assistant may suggest a plausible fix that changes the wrong layer or misses an affected caller.

Meeba Brain provides Cursor with repository-grounded structural context so Cursor can investigate the relevant relationships before proposing a change.

This helps Cursor identify the relevant code, understand potential impact, and propose better-informed fixes.

Meeba Brain does not guarantee that every fix is correct. Its purpose is to give Cursor better evidence and structural context for reaching the right fix.

What the MCP provides

Meeba Brain MCP provides access to repository knowledge graph capabilities, including:

  • Symbol relationships
  • Callers and callees
  • Dependencies
  • Repository structure
  • Structural context for code investigation

How to use Meeba Brain MCP

Meeba Brain MCP requires a connected, indexed repository.

The repository is connected and indexed on Meeba Brain, not inside Cursor.

1. Create your account

Go to:

https://meeba.ai/brain

2. Connect your repository

After signing in, connect the repository you want to investigate on Meeba Brain.

3. Wait for indexing to finish

Meeba Brain needs to build the repository's structural knowledge graph.

Wait until indexing is complete before connecting the MCP to Cursor.

4. Enable MCP and get your key

Open the MCP connection page:

https://meeba.ai/brain/connect

Enable MCP and copy the key provided by Meeba Brain.

Keep this key private.

5. Add Meeba Brain MCP to Cursor

In Cursor:

  1. Open Settings.
  2. Go to Tools & Integrations → MCP.
  3. Click Add Custom MCP or Add New MCP Server.
  4. Select the HTTP / remote MCP connection option.
  5. Enter the Meeba Brain MCP server URL shown on the connection page.
  6. Add the authentication header using your Meeba Brain MCP key.
  7. Save the configuration.

Use the exact server URL and authentication header shown in Meeba Brain.

6. Enable the server in Cursor

After saving the configuration, open the MCP settings and make sure Meeba Brain is enabled.

7. Ask Cursor a question about your codebase

Open your repository in Cursor and ask a question such as:

"Which services call refundOrder()?"

"Explain how this feature flows through the codebase."

"What could be affected if I change this API?"

"Trace the code flow from this route to the implementation."

"Why is this function being called?"

Start with one real function, dependency, or bug you want to understand.

Important distinction

Meeba Brain MCP is not a replacement for Cursor.

It is a repository knowledge graph integration that gives Cursor additional structural context.

Cursor remains responsible for the coding conversation, reasoning, and code changes.

Meeba Brain provides the repository intelligence that helps make that reasoning more grounded.

Best for

  • Developers working in unfamiliar repositories
  • Debugging code that spans multiple files or services
  • Understanding dependencies before making changes
  • Investigating the impact of a refactor
  • Developers who want more structural grounding from their AI coding assistant

Get started

Learn about Meeba Brain:

https://meeba.ai/brain

Connect your repository and enable MCP:

https://meeba.ai/brain/connect

Understand the relationships. Investigate the evidence. Make better-informed changes.

来源:README.md,提交 406680a

工具

5

search_code

Hybrid semantic + keyword search over the connected repository's actual indexed content. Use this for open-ended questions ("where is rate limiting implemented?", "how are uploads validated?") where you don't already know an exact symbol or file name -- for those, use get_symbol_definition or get_dependencies instead, they're more precise.

输入参数query必填top_k

get_symbol_definition

Finds where a function, class, or method is actually defined in this repo -- exact file, line range, and signature-relevant metadata (async, decorators, docstring if present). Use this before assuming a symbol's location/signature from memory or from a similarly-named symbol in a different file.

输入参数name必填

get_callers

Every place in this repo that calls the given function or method -- a COMPLETE list from the parsed call graph, not a best-effort guess. Use this before renaming/changing a function's signature, or when you need to understand a function's blast radius before modifying it.

输入参数function_name必填

get_callees

Every function/method the given function calls -- what it depends on to do its job. Use this to understand a function's behavior by seeing what it delegates to, before assuming what it does from its name alone.

输入参数function_name必填

get_dependencies

What a specific file imports/depends on. Use this to understand a file's place in the codebase before assuming what's available to it, or before moving/refactoring it.

输入参数file_path必填

版本历史

1
  1. v1.0.1最新Sep 16, 2026

评分

已满足适用检查项的 90%

该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。

  • 近 30 天内可连通必需25 分
  • 已声明认证方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 图标10 分
  • 文档15 分
  • 许可证10 分

    请在仓库或注册中心条目中声明许可证。

其他 Brain 集成