bgauryy/octocode-mcp
by Various
MCP server for semantic code research and context generation on real-time using LLM patterns | Search naturally across public & private repos based on your permissions | Transform
MCP
bgauryy/octocode-mcp
Added 1 June 2026
Overview
MCP server that performs semantic code research and generates context using LLM patterns. It allows searching across public and private repositories based on user permissions. It transforms accessible codebases into AI-optimized knowledge for finding real implementations and documentation.
Best for
Best for
Developers who need to search and understand codebases across repositories using natural language queries.
Use cases
- Searching across private repos for code patterns
- Generating context for complex code flows
- Finding real implementations and live docs across repositories
How to use
Install
npx octocode --help Tools exposed
OCTOCODE_HOMEGITHUB_API_URLENABLE_LOCALENABLE_CLONEWORKSPACE_ROOTALLOWED_PATHSREQUEST_TIMEOUTMAX_RETRIESOCTOCODE_OUTPUT_FORMAT
Tested with
Claude Code, Cursor, Windsurf, VS Code, ChatGPT
Notes
MCP server that performs semantic code research and generates context using LLM patterns. It allows searching across public and private repositories based on user permissions. It transforms accessible codebases into AI-optimized knowledge for finding real implementations and documentation.
854 stars on GitHub. Last updated 2026-05-23. Licensed MIT.
Use cases
- Searching across private repos for code patterns
- Generating context for complex code flows
- Finding real implementations and live docs across repositories
Pros
- Supports both public and private repos based on permissions
- Uses LLM patterns for semantic understanding
- Transforms codebases into AI-optimized knowledge
Cons
- Dependency on LLM patterns may introduce variability
- Requires appropriate permissions for private repos
- Focused on code research, not general development tasks
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Supports both public and private repos based on permissions
- Uses LLM patterns for semantic understanding
- Transforms codebases into AI-optimized knowledge
Cons
- Dependency on LLM patterns may introduce variability
- Requires appropriate permissions for private repos
- Focused on code research, not general development tasks
Pairs with
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