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Manage task records and seeded documents locally through controlled MCP tool functions.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "ContextForge MCP Lab" yet — see the docs or source repo.
Use ContextForge MCP Lab to create a set of test task records and import 20 sample documents from local JSON seed files, then return a summary of the import results.
A summary of created tasks and documents, import counts, failures, and status details.
Query all task records with pending status, filter items with priority greater than 3, update them to in-progress, and output the update list.
A list of matched tasks, their updated statuses, and the success or failure of each operation.
Check whether document records in SQLite match the JSON seed data, list missing, duplicate, or field-mismatched entries, and provide repair suggestions.
A consistency report with problematic entries, issue types, and recommended fixes.
Build, debug, and manage software tasks with natural language across LLMs.
Turn Markdown files into local MCP servers to define and run tools.
Turn any OpenAPI spec into a working MCP server.
Production-ready MCP server for query normalization, retrieval, and RAG prompt building.
Manage local todo lists through natural-language creation, updates, and queries.
Demo MCP server for calculations, time checks, notes, and code review prompts.