awesome-repositories.com
Blog
MCP
awesome-repositories.com

Discover the best open-source repositories with AI-powered search.

ExploreCurated searchesOpen-source alternativesSelf-hosted softwareBlogSitemap
ProjectMCP serverAboutHow we rankPress
LegalPrivacyTerms
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
colbymchenry avatar

colbymchenry/codegraph

0
View on GitHub↗
colbymchenry.github.io/codegraph↗

Codegraph

Codegraph is a local codebase indexer and static analysis graph database that serves as a context provider for AI agents. It parses multiple programming languages into a searchable knowledge graph of symbols and dependencies, exposing these relationships to AI tools through the Model Context Protocol.

The project distinguishes itself by aggregating relevant code snippets and symbol flows to reduce token usage for large language models. It automates the configuration of server settings and steering instructions across various AI agent platforms and command line editors to enable automatic codebase navigation.

The system covers broad capability areas including transitive dependency impact analysis, execution flow tracing, and framework route mapping. It utilizes a background daemon for incremental parsing and filesystem synchronization, ensuring the local symbol database remains current across multi-repo workspaces.

The application is delivered as a self-contained bundle to ensure environment consistency on host systems.

AI search

Explore more awesome repositories

Describe what you need in plain English — the AI ranks thousands of curated open-source projects by relevance.

Start searching with AI

Features

  • Model Context Protocol - Implements the Model Context Protocol to expose source code relationships and symbol flows to AI automation tools.
  • Codebase Indexing - Provides local knowledge graphs and symbol maps to AI agents to reduce token usage and improve codebase understanding.
  • Agent Context Providers - Dynamically aggregates symbols and code snippets to provide essential implementation context to AI agents.
  • AI Agent Integrations - Provides connectors and configuration interfaces to integrate AI coding assistants and editors with the codebase.
  • Codebase Impact Analysis - Traces transitive dependencies and import chains to identify which tests or functions are affected by specific code changes.
  • Codebase Dependency Mapping - Analyzes call paths, imports, and inheritance to map symbol dependencies across multiple programming languages.
  • Knowledge Graph Construction - Indexes source code across multiple languages into a local graph to enable fast symbol lookup and relationship tracing.
  • Code Impact Analysis - Traverses the knowledge graph to identify the full blast radius of a change by tracing callers and callees.
  • Static Analysis Databases - Provides a database of code structures that enables impact analysis and transitive dependency tracing across repositories.
  • Code Relationship Mappers - Traverses the knowledge graph to identify callers, callees, and the impact radius of code changes.
  • Model Context Protocol Servers - Acts as an MCP server that exposes a structured graph of code flows and symbols to AI agents.
  • Knowledge Graph Indexers - Parses source files into a searchable knowledge graph of symbols and edges using incremental updates.
  • Deterministic Symbol Indexing - Creates a consistent map of symbols and edges across multiple languages for accurate and repeatable symbol resolution.
  • Code Knowledge Graphs - Exposes a local index of source code symbols and relationships to AI agents via the Model Context Protocol.
  • Local-First Databases - Stores code relationships and definitions in a local database to enable fast querying without network requests.
  • Symbol Resolution - Generates symbols and edges for multiple languages using incremental parsing to create a structured map of source code.
  • Static Code Analysis - Maps dependencies, call graphs, and symbol relationships across multiple programming languages to understand complex software structures.
  • Change Impact Analysis - Identifies the blast radius of a change by surfacing all symbols that depend on a modified constant or function.
  • AI-Consumable Graph Formats - Formats complex graph data into markdown or JSON to ensure AI agents can efficiently consume codebase relationships.
  • Search Index Synchronizers - Monitors the filesystem for changes and triggers index updates to keep the internal data graph current.
  • Code Exploration Tools - Returns relevant source code for symbols while collapsing redundant implementations to optimize agent context.
  • Test Dependency Analysis - Traces import dependencies transitively to identify which test files are affected by changes to specific source files.
  • Daemon Management - Employs a background daemon to handle indexing and synchronization, preventing redundant resource usage.
  • Language Bridges - Connects execution flows across language boundaries, such as bridging high-level scripts to native modules.
  • Execution Flow Analyzers - Follows request-to-handler paths and bridges gaps in dynamic dispatch, such as callbacks and event emitters.
  • Framework Integration - Maps indirect calls and routes by applying heuristic patterns for specific software frameworks.
  • Filesystem Event Synchronization - Monitors the local file system for changes to trigger targeted updates of the knowledge graph.
  • Route Handlers - Identifies routing files and maps URL patterns to their corresponding handler functions or classes.
  • Heuristic Route Resolution - Applies language-specific patterns to link URL definitions in routing files to their handler functions and classes.
  • Agent Context and Memory - Local pre-indexed code knowledge graph to reduce token usage.
77,006 stars·5,117 forks·TypeScript·MIT·109 views

Star history

Star history chart for colbymchenry/codegraphStar history chart for colbymchenry/codegraph

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

Projects sharing features with Codegraph

These projects share indexed features with Codegraph. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • potpie-ai/potpiepotpie-ai avatar

    potpie-ai/potpie

    5,161View on GitHub↗

    Potpie is an LLM codebase analysis platform and multi-agent orchestration framework designed to act as an AI software engineer. It parses repositories into a structured code knowledge graph, enabling AI agents to perform multi-hop reasoning, dependency tracing, and grounded technical analysis across large codebases. The system distinguishes itself through a spec-driven development framework where agents generate detailed technical specifications and architecture plans before implementing multi-file code changes. It utilizes a durable execution engine to coordinate specialized AI personas for

    Pythonagentsai-agentsai-agents-framework
    View on GitHub↗5,161
  • kilo-org/kilocodeKilo-Org avatar

    Kilo-Org/kilocode

    15,616View on GitHub↗

    Kilocode is an autonomous engineering platform designed to orchestrate AI agents for complex software development tasks. It functions as a comprehensive system for automating coding, testing, and repository management by integrating directly with your codebase and terminal. The platform provides a unified gateway for model orchestration, allowing for the management of agentic workflows, event-driven automation, and persistent session state across distributed development environments. The platform distinguishes itself through its federated task management and policy-based access control, which

    TypeScriptaiai-ageai-coding
    View on GitHub↗15,616
  • coatisoftware/sourcetrailCoatiSoftware avatar

    CoatiSoftware/Sourcetrail

    16,471View on GitHub↗

    Sourcetrail is an interactive source code explorer and visualizer designed for indexing and navigating relationships between symbols and structures across large, multi-language codebases. It functions as a static analysis indexer and code dependency visualizer that maps calls and dependencies between source files to help reveal project architecture. The tool enables multi-language project analysis by using a language-agnostic indexing system to track symbols across different programming languages within a single interface. It allows for the discovery of software architecture and the explorati

    C++
    View on GitHub↗16,471
  • deusdata/codebase-memory-mcpDeusData avatar

    DeusData/codebase-memory-mcp

    48,292View on GitHub↗

    codebase-memory-mcp is a Model Context Protocol server that indexes source repositories into a persistent code knowledge graph, giving AI coding agents a queryable map of symbols, call paths and architecture so they read fewer files. Parsing uses bundled tree-sitter grammars covering more than 160 languages, and a built-in type layer links calls to their true definitions without a separate language server. Everything runs locally, with no cloud service or API key. Beyond the core graph, it offers read-only Cypher-style queries that return clear errors for unsupported syntax, and semantic code

    Caiderastclaude-code
    View on GitHub↗48,292
Compare all 30 related projects→

Frequently asked questions

What does colbymchenry/codegraph do?

Codegraph is a local codebase indexer and static analysis graph database that serves as a context provider for AI agents. It parses multiple programming languages into a searchable knowledge graph of symbols and dependencies, exposing these relationships to AI tools through the Model Context Protocol.

What are the main features of colbymchenry/codegraph?

The main features of colbymchenry/codegraph are: Model Context Protocol, Codebase Indexing, Agent Context Providers, AI Agent Integrations, Codebase Impact Analysis, Codebase Dependency Mapping, Knowledge Graph Construction, Code Impact Analysis.

Which projects share features with colbymchenry/codegraph?

Projects with overlapping indexed features include: potpie-ai/potpie — Potpie is an LLM codebase analysis platform and multi-agent orchestration framework designed to act as an AI software… kilo-org/kilocode — Kilocode is an autonomous engineering platform designed to orchestrate AI agents for complex software development… coatisoftware/sourcetrail — Sourcetrail is an interactive source code explorer and visualizer designed for indexing and navigating relationships… deusdata/codebase-memory-mcp — codebase-memory-mcp is a Model Context Protocol server that indexes source repositories into a persistent code… tirth8205/code-review-graph — This project is a static code analysis tool and local-first code indexer that builds a persistent dependency graph of… microsoft/vscode-copilot-chat — This project is an AI-powered IDE extension and LLM coding assistant that provides a conversational interface for…