Skip to main content
Glama
728,680 tools. Updated 2026-10-31 13:56

"Answer" matching MCP tools:

  • Settles the one popup, leader screen, or deal that question() shows by applying your chosen item, button, or accept/refuse response and returning the outcome or refusal.
    MIT
  • Retrieve AI-generated answers by searching your namespace of text documents or using direct AI model calls for question answering.
    Apache 2.0
  • Respond to an agent's pending question by accepting with schema-matched content, declining, or canceling, and optionally wait for the turn result.
    Apache 2.0
  • Ask a natural-language question about official statistics and receive a computed result with chart, code, and citations. Join series across agencies like BLS, Statistics Canada, and ONS.
    MIT
  • Reply to a project inbox question by questionId, record the response permanently, and mark it resolved; returns the response id and status.
    Apache 2.0
  • Generates a cited, prose answer to a natural-language question from fresh web results. Use it for synthesized answers; choose brief snippet-based or report depth with page reads and multiple searches.
    Apache 2.0

Matching MCP Servers

Matching MCP Connectors

  • Free AI readiness scan for any website. Paid reports for agents are coming soon.

  • Find out whether AI search recommends your brand, which buying questions competitors win instead, and what is stopping engines reading your site.

  • Respond to another session's ask by providing its ask ID and your reply, so the asker receives the information with other responses.
    MIT
  • Generates and executes caller-scoped SQL from a plain-language question, selecting relevant schema with the server's configured model and returning rows.
    Apache 2.0
  • Ask a natural-language question to get a synthesized answer grounded only in stored memories. Returns the answer with supporting memory sources for verification.
    MIT
  • Retrieve cited responses from your document collection, grounding each result solely in relevant passages. Returns grounded status, with no invented content when evidence is missing.
    MIT
  • Retrieve relevant passages and generate cited responses grounded solely in your documents, refusing when no supporting evidence exists.
    MIT
  • Resolve a task question by responding on its merits, or close it as withdrawn or replaced when it is stale or superseded. Requires the task key and question number.
    MIT
  • Respond to any natural-language question about your documents by retrieving relevant context from granted files and generating a concise reply with your local model.
    MIT
  • Respond to a pi agent's question to unblock it. Use the requestId from status and provide the chosen value.
    MIT
  • Research complex technical questions, compare options, and provide evidence-based recommendations with implementation steps for architecture decisions, migrations, and debugging.
    MIT
  • Reply to a question received from another coding-agent session, referencing the question ID to maintain the conversation thread.
    MIT
  • Produce scenario-specific summaries from medical evidence using a question ID and answer type. Supports clinical, research, and popular science contexts.
    MIT
  • Generate answers to questions by combining web search with AI language model capabilities.
    MIT
  • Provide Baekjoon problem analysis, complexity calculation, and working C++ and JavaScript code from a problem ID.
    ISC
  • Respond to a voice agent's mid-call question during an Uhura phone call by supplying the call ID, question event ID, and response text.
    MIT