NervusDB

NervusDB

nervusdb

Transforms codebases into queryable knowledge graphs to analyze code dependencies, relationships, and structure for impact assessment and automated workflow management.

Transforms codebases into queryable knowledge graphs using repomix and tree-sitter to extract code entities, relationships, and dependencies for call hierarchy analysis, impact assessment, code smell detection, and automated documentation generation.

6340 views2Local (stdio)

What it does

  • Analyze impact of code changes on related files
  • Find code definitions and references across projects
  • Map file relationships and dependencies
  • Generate project structure and statistics
  • Create task branches and PR workflows
  • Read and write project files with safety checks

Best for

Refactoring large codebases safelyCode review and impact assessmentAutomated documentation generationDeveloper workflow automation
Cross-language code analysisAutomated GitHub workflow integrationShadow index strategy for reliable data

About NervusDB

NervusDB is a community-built MCP server published by nervusdb that provides AI assistants with tools and capabilities via the Model Context Protocol. NervusDB transforms codebases into queryable knowledge graphs, enabling call hierarchy analysis, impact assessment, and It is categorized under developer tools, productivity. This server exposes 20 tools that AI clients can invoke during conversations and coding sessions.

How to install

You can install NervusDB in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

License

NervusDB is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

Tools (20)

workflow.startTask

创建任务分支并登记分支台账。

workflow.submitForReview

推送当前分支、创建 PR,并更新分支台账状态。

project.getStructure

返回项目文件结构及统计信息。 支持maxDepth限制树深度、limit限制文件数量、pathFilter过滤路径。 对于大型项目,建议使用这些参数减少响应大小。

project.readFile

读取绝对路径的文件(仅用于调试场景)。

project.analyzeImpact

Analyze the impact of changing a symbol (function/class/interface). Provides intelligent risk assessment, test coverage analysis, and actionable recommendations. Enhanced mode: provide "symbol" and "type" for deep analysis with risk scoring. Legacy mode: provide "filePath" or "functionName" for basic graph queries.

@nervusdb/mcp

Official MCP server for NervusDB - Code knowledge graph with repomix integration

npm version License: MIT

Features

  • Code Knowledge Graph: Build cross-language code knowledge graphs using @nervusdb/core and repomix
  • Project Insights: Analyze code impact, find related files, and explore project structure
  • Workflow Automation: Task management with branch creation and PR submission
  • Code Operations: Read, write files, and run tests with safety checks
  • Database Tools: Query and maintain the knowledge graph index
  • Shadow Index Strategy: Ensures reliable indexing with fingerprint validation

Prerequisites

  • Node.js 20.0.0 or higher
  • pnpm 8.0.0 or higher

Quick Start

Install Dependencies

pnpm install

Run the Server

# For development
pnpm start:stdio

# Build for production
pnpm build

Index a Project

pnpm synapse:index -p /path/to/your/project

Claude Desktop Integration

Add to your Claude Desktop configuration (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "nervusdb-mcp": {
      "command": "npx",
      "args": ["-y", "@nervusdb/mcp"]
    }
  }
}

Alternatively, if you've installed the package globally:

{
  "mcpServers": {
    "nervusdb-mcp": {
      "command": "nervusdb-mcp"
    }
  }
}

Installation Options:

# Option 1: Use npx (recommended, no installation needed)
# Just add the config above, Claude will run it automatically

# Option 2: Install globally for faster startup
npm install -g @nervusdb/mcp

Configuration

GitHub Authentication (for Workflow Tools)

Workflow tools (workflow.submitForReview) require GitHub authentication to create pull requests. The server supports 3 authentication methods with automatic fallback:

Method 1: Environment Variables (Recommended for CI/CD)

# Set GITHUB_TOKEN or GH_TOKEN
export GITHUB_TOKEN=ghp_your_personal_access_token

# Or in your shell profile (~/.zshrc or ~/.bashrc)
echo 'export GITHUB_TOKEN=ghp_xxx' >> ~/.zshrc

Method 2: GitHub CLI (Recommended for Local Development)

# Install gh CLI
brew install gh # macOS
# Or see https://cli.github.com/ for other platforms

# Authenticate
gh auth login

Method 3: Claude Desktop Configuration

Add environment variables to Claude Desktop config:

{
  "mcpServers": {
    "nervusdb-mcp": {
      "command": "npx",
      "args": ["-y", "@nervusdb/mcp"],
      "env": {
        "GITHUB_TOKEN": "ghp_your_personal_access_token"
      }
    }
  }
}

Authentication Priority:

  1. GITHUB_TOKEN environment variable (highest priority)
  2. GH_TOKEN environment variable
  3. gh auth token command (if gh CLI is authenticated)

If no authentication is available, workflow tools will provide clear error messages with setup instructions.

Available Tools

The NervusDB MCP server provides 13 tools across 4 categories:

1. Workflow Tools ⚙️

  • workflow.startTask - Create task branch and update ledger
  • workflow.submitForReview - Push branch and create pull request (requires GitHub authentication)

2. Project Tools

  • project.getStructure - Get project file structure with statistics
  • project.analyzeImpact - Analyze code impact based on knowledge graph
  • project.findRelatedFiles - Find files related to a target file
  • project.readFile - Read arbitrary file content

3. Code Tools

  • code.readFile - Read project file content
  • code.writeFile - Write content to project file (requires confirmation)
  • code.runTests - Run tests using Vitest and return results

4. Database Tools

  • db.getStats - Get index metadata and statistics
  • db.query - Execute typed or raw queries against knowledge graph
  • db.rebuildIndex - Rebuild project index with telemetry
  • db.getHealth - Check index health with fingerprint validation

Usage Example

// 1. Start a new task
workflow.startTask({
  taskId: '42',
  owner: 'alice',
  designDoc: 'docs/design/feature-42.md',
});

// 2. Analyze code impact
project.analyzeImpact({
  projectPath: '/workspace/my-project',
  functionName: 'calculateTotal',
  limit: 20,
});

// 3. Read a file
code.readFile({
  projectPath: '/workspace/my-project',
  file: 'src/services/orderService.ts',
});

// 4. Run tests
code.runTests({
  projectPath: '/workspace/my-project',
  filter: 'orderService',
});

// 5. Query the knowledge graph
db.query({
  projectPath: '/workspace/my-project',
  query: {
    type: 'typed',
    filter: { predicate: 'CONTAINS' },
    options: { limit: 100 },
  },
});

// 6. Submit for review
workflow.submitForReview({
  confirm: true,
  title: 'feat: optimize order calculation',
  reviewers: ['bob'],
});

How It Works

  1. Indexing: Uses repomix to collect project files and @nervusdb/core to build a knowledge graph
  2. Storage: Maintains shadow indices with fingerprint validation for data integrity
  3. Query: Provides typed and raw query interfaces to explore code relationships
  4. Workflow: Integrates with Git workflows for task management

Project Structure

nervusdb-mcp/
├── src/
│   ├── server/           # MCP server implementation
│   ├── tools/            # Tool implementations (workflow, project, code, db)
│   ├── services/         # Business logic services
│   ├── domain/           # Core domain logic (indexing, query)
│   └── utils/            # Shared utilities
├── bin/                  # CLI executables
├── docs/                 # Documentation
└── tests/                # Test suites

Development

# Install dependencies
pnpm install

# Run tests
pnpm test

# Check code quality
pnpm check

# Build for production
pnpm build

Documentation

Contributing

See CONTRIBUTING.md for development guidelines.

License

MIT

Alternatives

Related Skills

Browse all skills
ui-design-system

UI design system toolkit for Senior UI Designer including design token generation, component documentation, responsive design calculations, and developer handoff tools. Use for creating design systems, maintaining visual consistency, and facilitating design-dev collaboration.

18
ai-sdk

Answer questions about the AI SDK and help build AI-powered features. Use when developers: (1) Ask about AI SDK functions like generateText, streamText, ToolLoopAgent, embed, or tools, (2) Want to build AI agents, chatbots, RAG systems, or text generation features, (3) Have questions about AI providers (OpenAI, Anthropic, Google, etc.), streaming, tool calling, structured output, or embeddings, (4) Use React hooks like useChat or useCompletion. Triggers on: "AI SDK", "Vercel AI SDK", "generateText", "streamText", "add AI to my app", "build an agent", "tool calling", "structured output", "useChat".

6
ai-assisted-development

Leveraging AI coding assistants and tools to boost development productivity, while maintaining oversight to ensure quality results.

4
api-documenter

Master API documentation with OpenAPI 3.1, AI-powered tools, and modern developer experience practices. Create interactive docs, generate SDKs, and build comprehensive developer portals. Use PROACTIVELY for API documentation or developer portal creation.

4
teams-channel-post-writer

Creates educational Teams channel posts for internal knowledge sharing about Claude Code features, tools, and best practices. Applies when writing posts, announcements, or documentation to teach colleagues effective Claude Code usage, announce new features, share productivity tips, or document lessons learned. Provides templates, writing guidelines, and structured approaches emphasizing concrete examples, underlying principles, and connections to best practices like context engineering. Activates for content involving Teams posts, channel announcements, feature documentation, or tip sharing.

4
openai-knowledge

Use when working with the OpenAI API (Responses API) or OpenAI platform features (tools, streaming, Realtime API, auth, models, rate limits, MCP) and you need authoritative, up-to-date documentation (schemas, examples, limits, edge cases). Prefer the OpenAI Developer Documentation MCP server tools when available; otherwise guide the user to enable `openaiDeveloperDocs`.

4