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310,093 tools. Last updated 2026-07-28 08:46

"Resources for Learning Law" matching MCP tools:

  • Query structured training programs (learning paths) to retrieve metadata, enrollments, and student lists, with pagination and filters.
    MIT
  • Get the complete overview of the Dataflowr Deep Learning course: all sessions, modules, and their relationships, to provide students with a clear learning path.
    Apache 2.0

Matching MCP Servers

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    Local stdio MCP server for searching Japanese laws and retrieving article text from e-Gov Law Search. Includes related-law lookup for enforcement orders and regulations, with source attribution baked into every tool result.
    Last updated
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    MIT

Matching MCP Connectors

  • Extractive legal answers and semantic search over the public wiki.private.law corpus

  • Audited AI-regulation data: laws, bills, news and obligations across US, EU and 50+ jurisdictions

  • Retrieve lecture notes, explanations, and learning objectives for any module. Use this to answer conceptual questions about course topics.
    Apache 2.0
  • Generate zero-shot forecasts for countries with limited data by applying regime-similarity transfer learning. Ideal for countries lacking long event history.
    MIT
  • Delete a learning record using its unique ID. First, use list_learnings to find the correct ID.
    Business Source 1.1
  • Retrieve rightsizing recommendations for overprovisioned Azure resources to reduce costs by selecting optimized SKUs.
    MIT
  • Log learning entries with validation and duplicate detection. Appends to memory, returns status (added, duplicate, conflict, etc.).
    AGPL 3.0
  • Retrieve zoning classification, HCD compliance status, and state-law overrides for any US address.
    MIT
  • Resolve a learning entry by providing its timestamp. This updates the entry status to resolved in the MnemoQ memory system.
    AGPL 3.0
  • Scan a city to identify parcels qualifying for state-law incentives like SB-9 or AB-2011, returning a ranked list of development opportunities.
    MIT