MCP Research

Query: $ARGUMENTS

Goal: answer the query with minimum fetches. Targeted reads only — no broad crawling.

Sequence:

1. PARSE — Extract from $ARGUMENTS:

   • Target source type: github | url | mcp-tool | search
   • Specific artifact: endpoint, schema, function, config key, page section
   • If source is ambiguous → ask before fetching

2. LOCATE — One targeted lookup to find the exact resource:

   • GitHub repo: fetch https://api.github.com/repos/<owner>/<repo>/contents/<path> or raw file URL
   • API spec: fetch OpenAPI/AsyncAPI root, then only the relevant path object
   • DB schema: use available MCP tool (e.g. list-tables → describe only relevant tables)
   • Unknown source: one WebSearch with site: scoped query, pick top result

3. FETCH — Read only what answers the query:

   • For large docs: fetch the section anchor/fragment if URL supports it
   • For OpenAPI specs: extract only the relevant paths + components/schemas entries
   • For GitHub files: prefer raw URL over HTML — less noise, fewer tokens
   • Stop after 2 fetches if answer is found

4. SYNTHESIZE — Output:

SOURCE:  <url or tool:resource>
FINDING: <direct answer to the query — facts, not narrative>
SCHEMA:  <relevant fields/types if applicable>
NOTES:   <caveats, version constraints, gotchas>

Hard rules:

• Never fetch a page just to find where the real page is — resolve first, then fetch
• No recursive crawling — if a link looks relevant, include it in NOTES, don't follow it
• Skip auth/login pages — note the access requirement and stop
• If MCP tool is available for the source (DB, internal API), prefer it over web fetch
• Max 3 fetches per query — if not resolved: report what was found + what's still missing