What is Dependency Context?
Dependency Context is an MCP server that provides AI assistants with contextual access to your project's dependency documentation, enabling more accurate responses about libraries and frameworks used in your codebase.
How to use Dependency Context?
To use Dependency Context, create a dependency-context.json file in your project root to specify which dependencies to index. Then, add the MCP config to your editor and prompt the AI to initialize Dependency Context.
Key features of Dependency Context?
- Contextual access to dependency documentation for AI assistants.
- Ability to create a searchable index of project dependencies.
- Semantic search capabilities over indexed documentation.
Use cases of Dependency Context?
- Assisting developers in finding documentation for specific libraries.
- Improving the accuracy of AI responses regarding project dependencies.
- Streamlining the process of accessing and understanding library documentation.
FAQ from Dependency Context?
- Can Dependency Context work with any programming language?
Yes! Dependency Context can be configured to work with various dependency formats like package.json and requirements.txt.
- Is there a limit to the number of dependencies I can index?
No, but it's recommended to index only the dependencies you actively use to improve performance.
- How do I troubleshoot empty search results?
Ensure the indexing process completed successfully and verify your search query is relevant to the indexed dependencies.