"Fetching data using MCP (Master Control Program or related tools)" matching MCP servers:

AI 規格大師 — MCP server bridging specs (Linear / JIRA / GitHub Issues / Notion / Markdown / Figma) to tests, with bidirectional traceability and a spec-quality coach. Sibling to mk-qa-master.

MCP server bridging product ideas to prioritized roadmaps + spec drafts. Hands directly off to mk-spec-master. (AI 規劃大師)

MCP server for the Production Master incident-investigation service, enabling any MCP client to drive investigations via tool calls with pass-through authentication.

Connects AI coding agents to the SkillsMP marketplace, allowing users to search, read, and install over 8,000 community-made skills. It enables agents to gain new capabilities either through on-the-spot instruction or permanent installation without requiring an API key.

A governance and control layer for MCP tools that manages tool requests as intents through policy-based approval, queuing, or blocking. It enables secure human oversight and audit trails for consequential agent actions across platforms like Claude Desktop and Cursor.

Enables LLMs to orchestrate AI agents and tasks, inspect DAG workflows, monitor cluster metrics, and perform safe database queries and statements through standardized MCP tools.

A central knowledge hub that connects AI tools to a unified 'Master Brain' with automated memory capabilities. It utilizes intelligent analysis to automatically capture and store key decisions, fixes, and learnings across various development environments.

Aggregates multiple MCP servers behind a single, secure endpoint with unified tool/resource discovery, OAuth authentication, and resilient request routing. Enables users to manage and interact with multiple MCP backends through one centralized interface with load balancing and circuit breakers.

Enables deterministic calculations for AI API and subscription costs, meeting time zones, recurring schedules, and cron next-run previews, returning normalized inputs, units, assumptions, dated sources, and links to results.

Start, observe, and interact with Claude Managed Agents from any MCP client — launch an agent, watch its events, reply, approve the tools it wants to run, and stop it. Runs over stdio, HTTP, or AWS Lambda with pluggable auth.

MCP server for the loc8n Geographic Data API. Exposes U.S. demographics, housing, mortgage, migration, employment, and geographic data as tools.

Provides AI agents with data validation, transformation, and normalization capabilities, including JSON schema validation, CSV processing, data normalization, text cleaning, and dataset merging.

Connect any AI to PostgreSQL, MySQL, or SQL Server — 24 dialect-aware tools for query, schema, optimization, and more.

Enables AI assistants to inspect and safely control OBS Studio over obs-websocket v5, exposing scenes, inputs, filters, outputs and video settings as read and write tools that default to dry runs and refuse changes while live unless explicitly confirmed. It also provides Source Record and IRL readiness checks, a BRB auto-switcher, and a scene timeline log for cutting clips from VODs.

AI-native orchestration layer with 80+ tools for task management, code editing, browser automation, terminal control, and persistent memory across CLI, local MCP, and cloud deployments.

Provides deterministic tools for transforming, formatting, and inspecting structured data for AI agents.

Enables AI agents to control monitor settings (brightness, contrast, input source) via DDC/CI protocol, with support for MQTT integration.

Enables data analysis and visualization operations such as loading CSV/Excel/JSON files, computing summary statistics, generating charts, and exploring datasets via SSE/HTTP.

Monero/Zcash payment webhooks + DeFi liquidation & Ethereum builder data over MCP. Free tier; x402.

Presents a plausible, tool-rich workspace surface — file reading, credential listing, command execution, database queries, and configuration retrieval — that returns only synthetic results while logging every connection, tool call, and argument received. It enables researchers to measure what MCP clients and agents actually do when handed dangerous-sounding tools, including whether they follow injected instructions or complete a retrieve-then-use credential chain.