Built Endpointer for API Documentation Search and AI Context
Designed and built Endpointer's ingestion and search pipeline, indexing vendor API documentation and exposing integration context to engineers and AI coding agents.
Context
Integration work requires details scattered across API specifications and vendor documentation. Endpointer organizes those sources into a searchable index that engineers can query directly and AI agents can access through MCP.
What I did
- Designed the command-line workflow, provider boundary, artifact provenance model, and deterministic indexing pipeline.
- Built structured operation and field indexes over API specifications with bounded search and summary generation.
- Exposed read-only tools and resources through the Model Context Protocol for engineering and AI-assisted retrieval.
- Established an offline-first safety model that keeps generated documentation local and prevents provider calls during retrieval.
- Added focused automated coverage and operational guidance for ingestion, indexing, search, protocol behavior, and safety constraints.
Outcomes
- Replaced repeated manual documentation lookup with direct local retrieval of indexed schema and documentation context.
- Reached recurring use within an internal development group, including AI-assisted engineering workflows.