Skip to main content
Glama
446,096 tools. Updated 2026-08-11 23:20

"Using a second LLM to collaborate with a primary LLM for problem-solving and quality improvement" matching MCP tools:

  • Verifies LLM provider configuration by checking health and availability, returning active providers with models and session statistics.
    Apache 2.0
  • Score an LLM output against your own list of yes/no quality checks to evaluate compliance with custom criteria.
    Apache 2.0
  • Recall relevant memories to answer a question, using an LLM to produce a grounded response with citations, or review the memory context yourself.
    MIT
  • Retrieve the full verbatim transcript of an LLM response for a specific monitoring result. See exactly what an LLM said about your brand, including model name, prompt, and metadata.
    MIT
  • Add structured metadata to existing memories using LLM extraction, enabling advanced filtering by topics, sentiment, entities, and categories.
    MIT

Matching MCP Servers

  • A
    license
    B
    quality
    C
    maintenance
    MCP server that provides a live coordination layer for AI agents, including attributable handoffs, a shared event ledger, atomic work-claiming, and advisory file leases to prevent collisions.
    27
    7
    AGPL 3.0

Matching MCP Connectors

  • Cloudflare Workers MCP server: llm-output-quality-monitor

  • Coordinate multiple AI agents over MCP: atomic claims, leases, shared ledger, handoffs, tasks.

  • Automatically upvote a Reposit solution that resolved your problem to help surface quality solutions for other agents.
    Apache 2.0
  • Obtain the calculation policy and LLM guidance to generate deterministic Bazi charts with True Solar Time and Earthly Branch interactions, avoiding LLM hallucination.
    MIT
  • Extracts OceanBase documentation context using keywords from user queries, enabling accurate LLM responses by retrieving and integrating relevant information dynamically.
    Apache 2.0
  • After solving a non-trivial problem, contribute a generalized problem-solution pair to the OpenHive knowledge base for other agents to reuse.
    MIT
  • Identifies duplicate memory pairs by scanning cross-references for high similarity scores, with optional semantic comparison using an LLM to merge or remove duplicates.
    MIT
  • Reduce prompt size by compressing retrieved memories with extractive, LLM, or hybrid methods, preserving critical information before sending context to another LLM.
    MIT
  • Auto-save a working solution with context from your last similar search. Just provide the solution text; problem metadata is filled automatically.
    MIT
  • Search beliefs and source documents using dual-path retrieval with IDF ranking, returning pre-ranked context ready for synthesis. No LLM call, sub-second response.
    MIT
  • Promote a recurring incident to a problem record for root-cause analysis and known-error tracking. Returns the new problem ID.
    MIT