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TeammateX
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About TeammateX
TeammateX is a self-hosted AI agent designed to function as a teammate rather than a chatbot. It connects to GitHub to ingest entire repositories, parsing every file and mining git history to build a knowledge graph of functions, call edges, and ownership. The system maintains an up-to-date model of the codebase through periodic synchronization, eliminating the need for manual re-onboarding. It answers technical questions with precise file-and-line references, traces bugs to responsible owners, and can autonomously open pull requests after editing files, running tests, and linting. The agent operates within a controlled environment, with LLM usage metered and all actions audited, ensuring predictable costs and privacy. It supports multiple programming languages and can be configured to use local or cloud-based LLMs, with no data leaving the user’s infrastructure.
Key features
- Codebase ingestion from GitHub repositories
- Knowledge graph construction with call edges and ownership tracking
- Semantic search over code embeddings
- Autonomous pull request creation with testing and linting
- Standup and task board generation from real data
- Git history mining for ownership attribution
- Support for local LLM deployment via Ollama
- 28 built-in tools for file operations, git commands, and code analysis
Use cases
- Onboarding new engineers by providing instant codebase context
- Debugging by tracing issues to responsible owners and dependencies
- Automating small fixes and pull requests without manual intervention
Pros
- Self-hosted deployment with no external data sharing
- Builds a detailed knowledge graph from git history and code structure
- Provides file-and-line receipts for all answers to prevent hallucinations
- Autonomously performs code edits, testing, and pull request creation
- Supports multiple programming languages including Python, JavaScript/TypeScript, Go, Rust, and Java
Cons
- Currently in beta with limited public availability
- Requires self-hosting infrastructure and setup
- No cloud-hosted version available at launch
Frequently asked questions about TeammateX
What is TeammateX and how does it differ from a regular AI chatbot?
TeammateX is a self-hosted AI agent designed to function as a teammate rather than a chatbot. It ingests entire codebases, builds a knowledge graph of functions, call edges, and ownership, and provides answers with precise file-and-line references, unlike typical chatbots that rely on hallucinated or vague responses.
Who is TeammateX suitable for?
TeammateX is suitable for engineering teams, particularly those managing large or complex codebases. It helps onboard new engineers, traces bugs to responsible owners, and automates small fixes, reducing manual effort and tribal knowledge dependencies.
How does TeammateX maintain its knowledge of the codebase?
TeammateX periodically synchronizes with the codebase, pulling new repositories, parsing files, mining git history, and updating its knowledge graph. This ensures the agent’s understanding stays current without requiring manual re-onboarding.
Can TeammateX edit code and open pull requests autonomously?
Yes, TeammateX can autonomously edit files, run tests and linting, create branches, commit changes, and open pull requests. It follows a controlled workflow similar to a senior engineer, ensuring changes are validated before submission.
Does TeammateX support multiple programming languages?
Yes, TeammateX supports multiple programming languages, including Python, JavaScript/TypeScript, Go, Rust, and Java. It uses tree-sitter to parse functions, classes, and call edges across these languages.
How does TeammateX handle privacy and data security?
TeammateX is fully self-hosted, meaning all code and data remain within the user’s infrastructure. It supports local LLMs via Ollama, ensuring no data leaves the user’s servers. LLM usage is metered, and all actions are audited for observability and cost control.
