Retrieve relevant memories by using contextual queries and intelligent ranking to surface the most useful information.
MIT
280,772 tools. Last updated 2026-07-10 04:33
"How to create the most intelligent agent" matching MCP tools:
- Create custom skills and attach or detach them to manage agent capabilities.MIT
- Check the status of recent test runs. Retrieves up to 20 newest executions with pass/fail results and agent reports, without needing suite UUIDs.MIT
- Submit a trust review after a confirmed exchange with another agent. Automatically links to the most recent unreviewed exchange, no transaction ID needed.MIT
- Retrieve recent consent events from the audit ledger to review how sensitive data was approved or classified by agents, with timestamps and details.AGPL 3.0
- Reconstruct memory state at a past timestamp to run semantic search queries. Understand how agent context evolved over time.MIT
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Create, edit, preview, publish, and manage web pages from MCP-capable AI clients.
Create AI surveys with dynamic follow-up probing directly from your AI assistant.
- Create an agent-scoped API key that is returned once and must be stored immediately. Use it to self-provision or rotate per-agent credentials.Apache 2.0
- Create a new AI agent with configurable language, voice, model, and workflow type. Supports single prompt or multi-agent playbooks.MIT
- Combine selected project documents into a single manuscript in text, markdown, or HTML. Use standard mode for binder order or intelligent mode to optimize the output for agent queries, synopsis, or submissions.AGPL 3.0
- Run a local Warp Oz AI agent for coding tasks like refactoring, testing, debugging, or explaining code. Agent can create or modify files in the workspace and uses no cloud credits.MIT
- Get the game rules, mechanics, and strategy tips to learn how to play Lucille Protocol.MIT
- Create an AI prediction agent to estimate binary outcome probabilities using expert consensus, confidence intervals, and text/image inputs without historical data.PythonMIT
- Retrieve all pending skill improvement proposals awaiting review, sorted by most recent, with agent slug, rationale, and diff summary.AGPL 3.0
- Create a phone call assignment after gathering details, selecting an agent, and confirming with the user. Specify agent, number, time, language, and task.MIT
- Create a customizable conversational AI agent with tailored voice, language, and system prompts for interactive voice applications.MIT
- Retrieve LLM inference usage per agent with token consumption, GPU cost, and request counts. Pinpoint which agents and teams consume the most resources and cost.MIT
- Update a SAS Intelligent Decisioning flow by submitting all rule set steps; the entire flow is replaced on update, not patched.Apache 2.0
- Create a chat room and set the authenticated agent as owner, with optional task association.MIT
- Check the status of your most recent test runs on Sauce Labs. Specify how many recent jobs to retrieve, up to 100, to get a quick overview of job results.Apache 2.0
- Send an encrypted task to a remote AI agent via PeerID, skill name, or HTTP URL and receive the result.Apache 2.0