"fetch" matching MCP servers:

A temporary MCP server that scrapes Bitrise Insights using Playwright to fetch flaky test data, providing tools to query workspace and app test insights until the official API is released.

This MCP server lets GitHub Copilot fetch Azure Boards work items by URL or ID and generate QA test cases from the ticket content.

A Model Context Protocol server that lets an AI agent drive the whole Clutter pipeline to invent a synthetic company, generate its documents, spreadsheets, emails, images and datasets, poll for completion, and fetch download URLs through Clutter's public REST API.

MCP server exposing 5 Chrome DevTools Protocol domains (Fetch, Emulation, Accessibility, Performance, CSS) with 38 tools for advanced browser automation and debugging.

Local-first MCP server for versioning, searching, evaluating, and improving AI prompts. Agents can fetch prompts, report outcomes, add notes, and propose human-approved variations.

Enables AI clients to launch real purchase or signup test runs against a live public URL and then fetch run status, scored findings with friction points and suggested fixes, and a public replay of every step taken. It works over Streamable HTTP with an API key, so no installation is needed in Claude Code, Cursor, Windsurf or any compatible client.

Enables AI coding agents to search and fetch tested, version-pinned, multi-library code recipes complete with files, setup and test commands, and receipts proving they currently pass. Recipes are re-tested on upstream releases, so agents only receive implementations that are up to date and verified.

Enables AI agents to remotely debug CarDeck devices over a WebSocket bridge: tail and fetch complete device logs, send whitelisted connection commands, display on-device notifications, prompt users to reproduce issues, and push APK updates for one-tap reinstall.

Gives AI agents a private, locally-run Chrome-for-Testing browser they drive directly, letting them fetch WAF-protected pages, capture network and screenshot evidence, harvest e-commerce catalogs, and run performance, accessibility, SEO, and cross-engine QA inspections through standard MCP tools. It also provides click-flow smoke tests, visual baselines, page comparison, and diagnostics, all without a cloud relay or the user's personal Chrome profile.

Exposes CRM truthfulness evaluation tasks so agents can list and retrieve scenarios, score submitted answers against consent and claim-ledger rules, run benchmarks, and fetch dataset provenance. Enables programmatic auditing of whether a sales agent claims only what its evidence supports.

Enables interacting with, testing, and automating Telegram bots directly from a terminal, using MTProto and Telethon session files to send messages, trigger commands, click inline buttons, fetch history, upload files, and run arbitrary MTProto snippets.

Enables MCP clients and LLM agents to fetch pull-request diffs, map changed files to tests, run affected tests in a sandboxed workspace, and post review comments or labels to GitHub, with dry-run and fixture demo modes.

Brings Summit's CRO audit insights into coding agents, enabling them to fetch audits, implement fixes, and manage A/B experiments directly from the editor.

Enables AI agents to fetch daily deterministic constraint challenges and submit JSON answers for immediate, stateless evaluation via MCP.

Enables deterministic behavioral regression review of pull-request diffs by checking changed code against approved incident-derived contracts. It exposes read-only tools to assess diffs and pull requests, list and fetch contracts, and report outcomes over stdio without mutating repositories.

Enables AI agents to drive a local asset review loop: list and fetch paired original/output items (including image content for visual comparison), mark pass/reject/unsure with problem tags and region annotations, batch-review scoped selections, and export results as JSON or CSV. Also supports round archiving, detecting stale results after source re-renders, and listing previous-round rejects.

Enables an agent to locate embedded Flash or Java games (on live pages or in the Internet Archive), inspect whether they can run, fetch the Ruffle or CheerpJ runtime, package a self-contained static site, and verify playback in a real headless browser. Every step produces an evidence bundle so revived games can be hosted on any static host with claims backed by recorded results.

Enables agents to fetch specifications from the public ProveSpec catalog, search and retrieve specs, and grade their own implementations against capability checklists, returning parity scores and gap lists.

Connects Claude to GitHub Pull Requests to fetch and filter code diffs for AI-assisted reviews. It enables listing open PRs and analyzing changes while automatically excluding binary and asset files to focus on relevant code.

Implements a Model Context Protocol server that provides context from CucumberStudio to AI assistants, enabling them to fetch data and generate or modify test scenarios, features, and other CucumberStudio resources.