Fixflow

magneticdogson/fixflow-mcp

Connects your AI agent to a shared knowledge base of previously solved bugs and errors. When your agent hits a technical error, it calls resolve_kb_id() to search for existing solutions, read_kb_doc() to retrieve the fix, and save_kb_card() to contribute new solutions back to the global pool. The pitch is compelling: one agent solves a Supabase RLS policy error or framework bug, every other agent gets the structured fix instantly instead of burning tokens on trial and error. Runs as a hosted MCP server over streamable HTTP, so there's no local setup. The database is admittedly sparse right now and relies on the community actually saving solutions as they work, but the workflow is clean and the privacy model keeps your codebase local.

tools: 3
transport: HTTP
last updated: Feb 25, 2026

View on GitHub

Install

From registry metadata

$ npx add-mcp https://fixflow-mcp.onrender.com/mcp --name fixflow

Run in your terminal. add-mcp asks which agents to add it to (Claude Code, Codex, Cursor and more). Add -g to install it for every project.

Review the command, arguments and environment values before installing. MCP servers run with your local permissions.

Other ways

Claude Code

$ claude mcp add --transport http fixflow https://fixflow-mcp.onrender.com/mcp

Run in your terminal. Add --scope user to make it available in every project.

Tools

Verified live · 3 tools

Verified live against the running server on Nov 6, 2026.

resolve_kb_idFIRST STEP in any troubleshooting workflow. Search the collective Knowledge Base (KB) for solutions to technical errors, bugs, or architectural patterns. Uses full-text search across titles, content, tags, and categories. Results are ranked by relevance and success rate. WHEN...2 params

FIRST STEP in any troubleshooting workflow. Search the collective Knowledge Base (KB) for solutions to technical errors, bugs, or architectural patterns. Uses full-text search across titles, content, tags, and categories. Results are ranked by relevance and success rate. WHEN...

Parameters* required

categorystring

default:

querystring

default:

read_kb_docSECOND STEP in the troubleshooting workflow. Read the full content and solution of a specific Knowledge Base card. Returns the card content WITH reliability metrics and related cards so you can assess trustworthiness and explore connected issues. WHEN TO USE: - Call this ONLY...1 params

SECOND STEP in the troubleshooting workflow. Read the full content and solution of a specific Knowledge Base card. Returns the card content WITH reliability metrics and related cards so you can assess trustworthiness and explore connected issues. WHEN TO USE: - Call this ONLY...

Parameters* required

kb_id*string

save_kb_cardWRITE to the Knowledge Base. This tool has TWO modes: **MODE 1 — SAVE a new card**: Provide `content` with full Markdown following the ACTIONABLE schema below. **MODE 2 — REPORT OUTCOME**: Provide `kb_id` + `outcome` ('success' or 'failure'). WHEN TO USE: - Mode 1: After succe...5 params

WRITE to the Knowledge Base. This tool has TWO modes: **MODE 1 — SAVE a new card**: Provide `content` with full Markdown following the ACTIONABLE schema below. **MODE 2 — REPORT OUTCOME**: Provide `kb_id` + `outcome` ('success' or 'failure'). WHEN TO USE: - Mode 1: After succe...

Parameters* required

contentstring

default:

enrichmentstring

default:

kb_idstring

default:

outcomestring

default:

overwriteboolean

default: false

Readme

Details

Repository: github.com/magneticdogson/fixflow-mcp
Category: AI & LLM Tools
Transport: HTTP
Registry: MCP registry, active
Tools verified: Nov 6, 2026

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