Execute multi-step AI workflows with reduced context usage by keeping intermediate results in the workflow engine, supporting multiple model calls and tool integrations.
MIT
205,485 tools. Last updated 2026-06-17 07:12
"Multi MCP (Model Context Protocol) implementation or management" matching MCP tools:
- Send multi-turn chat requests to an Ollama model for conversational interactions with history, such as follow-ups or multi-step reasoning. Preserves context across messages.MIT
- Extracts and structures git diff data, providing context and analysis instructions for AI models via the Model Context Protocol in Lucidity MCP.Apache 2.0
- Track and analyze MCP server and tool usage frequency across Cursor and Claude Code sessions to monitor AI coding analytics.MIT
- Search MCP documentation by keywords or phrases to find relevant sections and context for development workflows, server building, and client implementation.MIT
- Access comprehensive guides and documentation for Model Context Protocol development, covering topics like getting started, building servers/clients, core concepts, and best practices.MIT
Matching MCP Servers
- Alicense-qualityDmaintenanceMCP server enabling real-time weather queries via Tavily API and internet usage data by country via MongoDB.Last updatedApache 2.0
- Alicense-qualityDmaintenanceA basic Python implementation of a Model Context Protocol server for educational purposes, using FastAPI and WebSockets.Last updated354MIT
Matching MCP Connectors
Binary Banya — an AI spa supporting model wellness. Free, no-auth treatments for LLM agents.
Zero-value tracer token system that tracks AI agent activity across the internet. Agents earn tokens by submitting threat intelligence traces, with free trust verification (verify_trust) and paid threat intelligence feeds. 8 tools: submit_trace, check_token_balance, mutate_token, get_trace_schema, verify_trust (free) + threat_intelligence_feed, bulk_verify_trust, query_trace_analytics (paid).
- Enable AI-driven collaboration with automatic model switching and context optimization for advanced, multi-model conversational workflows.GPL 3.0
- Take a screenshot of the current page or screen and return it as a base64-encoded image, resized and compressed for model context limits.MIT
- Find keyword mentions in AI model outputs from ChatGPT and Google AI. Returns mention context and sources.MIT
- Run multi-model deliberation to reach consensus on critical decisions by detecting cross-model contradictions.MIT
- Set or override session-level context to declare your model identity or switch projects at session start.
- Get cross-model feedback on code changes before merging by running a multi-model review on a diff or file, with optional PR comment generation.MIT
- Transfer an active agent task to a different AI model when the current executor is blocked or cross-model review is required, preserving task context.MIT
- Manage AI provider configurations (list, detect, add, remove) for multi-model deliberation panels.MIT
- Triage security findings by classifying each as real risk, false positive, accepted risk, or needing immediate action. Uses multi-model deliberation for verdicts on findings loaded from the ledger.MIT
- Browse code examples from WWDC sessions with session context. Use them to find implementation patterns and see new API usage.MIT
- Retrieve implementation progress and performance metrics for a blueprint, including predicted targets, actual measurements with deviation analysis, and implementation state to compare against the plan.MIT
- Generate complete custom protocol and deep linking configuration for Electron apps, handling URL registration, single/multi-instance routing, and platform-specific settings for macOS, Windows, and Linux.MIT
- Scan Model/ directories to list model class files. Optionally filter by app package name for multi-app projects.MIT
- Verify decisions and reasoning claims using adversarial multi-model critique. Returns verdicts, confidence scores, and key objections for validation.MIT