"Multi-platform information search across productivity and knowledge tools" matching MCP servers:

Enables AI agents to interact with 1C: Enterprise development environment, including running tests, managing launch profiles, building configurations, and performing database operations through the 1C: Platform Tools extension.

MCP server for operating and testing Android devices with AI agents. Provides observation and action tools for interactive control and spreadsheet-driven test runs.

Enables Claude Code to read and write issues on the Testing Platform via natural language, including listing projects, filtering issues, creating and updating issues, and adding comments.

Exposes six evidence-oriented tools over stdio so MCP clients can navigate unfamiliar code, ask typed questions about repository evidence, review completed changes, and select existing tests.

Enables generating JSON Schema from sample data, generating TypeScript types, validating data against schemas, creating mock data from schemas, and comparing schemas for differences.

Webhook management and testing tools for AI agents. Provides tools for sending, validating, generating, and debugging webhooks.

Enables AI agents to safely read, search, and inspect a local git repository, including PR-style diffs and changed-file summaries. It also supports opt-in allowlisted test runs.

Enables AI/agent-generated content to be reviewed by a cross-vendor committee of LLMs, returning verdicts, issues, votes, and cost estimates through an MCP review tool for consensus-based hallucination defense before shipping.

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

Enables validating JSON/JSONC, getting/setting values with jq-like paths, pretty-printing or minifying, validating against Ajv JSON Schema, and diffing local files or inline strings without network calls.

Enables coding agents to run Playwright e2e tests, validate Supabase RLS policies with role-based SQL, typecheck TypeScript, execute npm scripts with parsed test output, and validate Next.js builds, all through a structured MCP interface.

Enables reproducible evaluation of AI agents on multi-source evidence investigation tasks, providing Docker-based scenarios, MCP tools, and automated scoring for payout reconciliation, performance-claim verification, and incident reconstruction.

Enables AI agents to run configured test suites, inspect failures and logs, compare runs, and draft or file bug reports only after human confirmation, with safeguards such as selector validation, environment isolation, timeouts, and redaction.

MCP server providing code review, auto-fix, test running, linting, formatting, and refactor suggestions for Claude Code.

Enables AI agents to interact with Ethereum smart contracts through Anvil, providing capabilities to read Solidity code, simulate and execute transactions, manipulate blockchain state, query events, and test contracts in isolated environments for development and auditing workflows.

Provides 32 remote tools that let agents validate common data formats, optimize or minify code and content, and generate synthetic test data such as fake records, IDs, and passwords.

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

Enables users to run synthetic support-agent evaluations, preserve and inspect traces, score results deterministically, inject failures, and enforce release review gates through MCP tools, resources, and prompts.

Code linting and style checking tools for AI agents, exposed as an MCP server. Supports style checks, naming conventions, complexity analysis, dead code detection, and import analysis.

This MCP server builds a local flakiness knowledge graph from Playwright test run history and enables AI agents to query flaky tests, failure patterns, trends, and correlated git commits, helping diagnose test reliability without manual analysis.

Bridges AI agents with VS Code's debugger, enabling breakpoint management, step execution, variable inspection, and stack tracing via CLI commands.

Provides AI agents with web accessibility analysis tools via MCP, enabling checks for alt text, heading hierarchy, color contrast, ARIA validation, and form accessibility.

Runs a multi-agent code review pipeline via MCP, analyzing git diffs for security, quality, and logic issues and returning a pass/fail verdict.

A lightweight multi-provider MCP testing fixture with two providers (eva_air and uk_railway), each exposing 5 tools using in-memory fake data, designed for verifying MCP client tool discovery, tool calls, and multi-provider routing.

Enables AI agents and test runners to control Android devices via local ADB, including listing devices, tapping, swiping, typing, sending system keys, launching apps, and dumping UI hierarchy. Communicates over MCP stdio without exposing network listeners.

Exposes a version-controlled knowledge base as MCP tools so agents can read merged identity/state summaries and next recommended actions at runtime, plus run deterministic schema validation and cross-reference link checks. This lets agents fetch live state and verify integrity via self-describing calls instead of re-reading raw files.

Enables validating IFC models against IDS requirements with coverage reporting, auditing LOD by project stage, and extracting quantity take-offs, including combined audit summaries and full BIM health checks. It exposes these capabilities as MCP tools for Claude Desktop, producing Excel, HTML, and BCF reports.

An MCP server that complements Epic's official Unreal Engine MCP server with 78 additional tools across 14 subsystems for build/cook/package, cinematics, Niagara, automation testing, source control, profiling, World Partition, and project maintenance, using Unreal's built-in Python and Remote Control plugins.

A Model Context Protocol (MCP) server that provides testing and debugging tools for Stripe integrations, including test clock management, customer and product management, and subscription testing.

Enables controlled interception, review, and editing of web_search and fetch_page responses through a native desktop console, supporting live retrieval, synthetic or hybrid results, context sessions, and fault injection for AI agent robustness experiments.