Elmoaid/TempoGraph
by Various
Your AI agent finds the right files. Every time. Code graph context engine with 24 MCP tools — 170+ languages, triple search, +27% F1 improvement.
MCP
Elmoaid/TempoGraph
Added 1 June 2026
Overview
TempoGraph is a code graph context engine that helps AI agents find the correct files in a codebase. It provides 24 MCP tools, supports over 170 programming languages, and uses a triple search method. The tool claims a 27% improvement in F1 score for file retrieval tasks.
Best for
Best for
Developers building AI agents that need precise file retrieval in polyglot codebases.
Use cases
- Improving AI agent accuracy in locating relevant source files.
- Enhancing code search across large multi-language repositories.
- Integrating with MCP-based development workflows for context-aware assistance.
Notes
TempoGraph is a code graph context engine that helps AI agents find the correct files in a codebase. It provides 24 MCP tools, supports over 170 programming languages, and uses a triple search method. The tool claims a 27% improvement in F1 score for file retrieval tasks.
1 stars on GitHub. Last updated 2026-05-08. Licensed AGPL-3.0.
Use cases
- Improving AI agent accuracy in locating relevant source files.
- Enhancing code search across large multi-language repositories.
- Integrating with MCP-based development workflows for context-aware assistance.
Pros
- Supports a wide range of 170+ programming languages.
- Provides 24 MCP tools for flexible integration.
- Triple search method may improve retrieval accuracy.
Cons
- Only 1 star on GitHub, indicating limited community adoption or early stage.
- Requires Python environment and MCP setup.
- Performance claims may not generalize to all codebases.
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Supports a wide range of 170+ programming languages.
- Provides 24 MCP tools for flexible integration.
- Triple search method may improve retrieval accuracy.
Cons
- Only 1 star on GitHub, indicating limited community adoption or early stage.
- Requires Python environment and MCP setup.
- Performance claims may not generalize to all codebases.
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