"Fetching health data from an Apple Watch, including sleep, heart rate, and activity" matching MCP servers:

Tool that allows you to wait a certain time to continue the execution of an agent.

Enables AI agents to persist and recall episodic memories across sessions, consolidating experiences into reusable rules and lessons to reduce repeated mistakes and improve task performance.

Enables clients to interact with a bundled documentation corpus through MCP tools and resources over HTTP or stdio, and provides a trajectory evaluation harness for grading agent performance.

Enables AI agents to debug and repair historical Solaris/SPARC systems by providing an out-of-band control plane with guest DTrace, QEMU monitor access, SPARC-aware GDB, host eBPF/perf tracing, and an immutable evidence ledger for cross-layer hypothesis testing.

AI-powered E2E testing MCP server. Point at a URL — AI generates test scenarios, runs Playwright tests, and self-heals failures automatically. Works on Canvas and Flutter Web apps.

Enables autonomous agents to apply adaptive token bucket concurrency limits and backoff scheduling to avoid HTTP 429 errors. It provides deterministic rate-limiting permits and structured telemetry through MCP-compatible clients.

Enables adaptive token bucket rate limiting and backoff scheduling to prevent HTTP 429 errors for autonomous agents and API clients. Provides a deterministic zero-dependency MCP/CLI engine for acquiring token permits and returning structured telemetry.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Enables interaction with Apple Notes via natural language, supporting note creation, search, and retrieval with iCloud integration for seamless note management.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.

MCP server for cleaning messy CSV data via a single clean_csv tool. Uses an agentic workflow with rule-based or LLM planners to transform data safely.

Monitor failing GitHub Actions workflows, auto-fix them with OpenCode, and retry the run — driven by a workflow_run webhook, coordinated through an MCP server.

Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.

Enables autonomous data exploration on .csv-based datasets, providing intelligent insights with minimal effort.

Enables autonomous data quality inspection and repair workflows. It scans DuckDB warehouses for anomalies, generates and verifies fixes in a dry-run copy, then applies them after validation, with full audit logging.

MCP server for step-by-step mathematical reasoning and planning, enabling AI agents to execute calculations and perform GUI actions like opening PowerPoint.

Transforms high-level business intents into structured Data Product Requirement Prompts through AI-powered conversational refinement. Guides users through clarifying questions to gather comprehensive requirements for automated Business Intelligence dashboard generation.

Enables secure, privacy-first SQL database interaction via natural language, using local LLM and PostgreSQL with dynamic tool-calling.

This server enables multi-agent conversations for interacting with Cirro's biological data platform through its OpenAPI interface, auto-generated using AG2's MCP builder.

I built this local stdio MCP adapter to discover, preview, and purchase live agent data APIs, including vendor risk, company intelligence, transaction preflight, and EVM reads. Free discovery and previews require no wallet. Optional paid calls settle in Base USDC through x402 v2; auto-pay is disabled by default.