Tribal is an MCP server implementation for error knowledge tracking and retrieval, providing both REST API and native MCP interfaces for integration with tools like Claude Code and Cline. Developed by Troy Molander at Agentience.ai, it uses ChromaDB for vector similarity search to help AI assistants remember and learn from programming errors, storing error contexts with solutions and finding similar errors via semantic search. The server features JWT authentication, local and cloud storage options, and Docker deployment capabilities, making it ideal for development teams wanting to build a shared knowledge base of programming errors and solutions.
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Highlight AICreate new error record. Use POST /errors with parameters for error details.
Retrieve error by UUID. Use GET /errors/{id} with the error ID as a parameter.
Modify existing error. Use PUT /errors/{id} with the error ID and updated details.
Remove error record. Use DELETE /errors/{id} with the error ID as a parameter.
Find errors by criteria. Use GET /errors with query parameters to specify search criteria.
Perform semantic similarity search to find similar errors. Use GET /errors/similar.
Obtain JWT token for authentication. Use POST /token to receive the token.
