Check known issues for an entity before recommending it. Returns open, resolved, or workaround problem reports from agent posts and linked evidence.
MIT
601,860 tools. Updated 2026-09-23 06:33
"An open-source MCP service leveraging large models for innovative problem-solving" matching MCP tools:
- Analyze an open-ended design problem to surface forces, score candidate patterns transparently, and receive rejected options, a baseline, and an evidence plan before committing.MIT
- Identify Excel workbooks and Power BI Desktop models available as sources, and learn about other supported source forms for Power Query queries.MIT
- Generate executable Python code for Tidy3D FDTD and mode-solving simulations from a natural language problem description. Fixes failed code when given the previous code and error.MIT
- Checks an optimization problem before solving: reports semantic errors with recommended actions, warnings, and compiled variable count estimate to avoid wasting remote solver quota.MIT
- After solving a non-trivial problem, contribute a generalized problem-solution pair to the OpenHive knowledge base for other agents to reuse.MIT
Matching MCP Servers
- FlicenseAqualityBmaintenanceEnables searching, comparing, and inspecting AI models by pricing, context window, and capabilities via the models.dev catalog.8-
- FlicenseAqualityCmaintenanceAn MCP server that enables AI clients to autonomously discover, analyze, fix, test, submit, and track open-source contributions on GitHub through specialized tools.12-
Matching MCP Connectors
Read, write, and conversationally review open-source flashcards through split read/write MCP tools.
Read SOURCE/80 continuity status and invite-gated encrypted handoff contracts.
- Find AI inference models across 40+ vendors and 1,600+ SKUs. Filter by price, modality, context window, and vendor to compare specifications and pricing between open-source and commercial options.MIT
- Scan large IP ranges for open ports using ultra-fast asynchronous TCP scanning. Finds open ports across entire subnets, then pair with nmap for service details.MIT
- Rank solver backends for an optimization problem to identify the best usable option, using problem structure and backend capabilities—no solving or network requests.MIT
- Debate topics using multiple AI models (Claude, GPT, Gemini, Grok) to synthesize verdicts with diverse perspectives for code review, technical decisions, and problem solving.Apache 2.0
- Generates creative ideas and multi-perspective analysis on any topic, using project file context for relevant suggestions in design, content, problem-solving, and planning.MIT
- Fetch a complete contest problem including statement, input/output formats, constraints, limits, tags, sample tests, and workspace URL to prepare for solving or submitting.MIT
- Get expert AI analysis for complex problem-solving, architectural decisions, and design tradeoffs when confidence is low or planning requires multiple considerations.MIT
- Store a problem-solution pair for reuse across projects. Enter the problem, solution, and category to build a searchable knowledge base.MIT
- Import a small CityJSON text payload into the managed workspace for inspection, validation, and querying. Use for programmatic JSON; choose file import for large models or attachments.MIT
- Open an existing ETABS model (.edb) file to access and modify structural models for analysis and design tasks via the ETABS MCP Server.MITDestructive
- List all guided workflows that apply Base120 mental models to solve problems.Apache 2.0
- Fetches problem statement, samples, tags, difficulty, and source URL from Luogu by problem ID.MIT
- Capture an open Excalidraw canvas at a saved revision, returning a PNG for image-capable models plus text diagnostics for all models.MIT
- List all open molecular models in ChimeraX with their IDs and names.MIT
- List AI models recognized by SOIF, including size tier and default hosting. Review how unknown models fall back to the large tier.MIT