"Information about Microsoft Teams" matching MCP servers:

Enables AI agents to debug code inside VS Code by setting breakpoints, stepping through execution, inspecting variables, and evaluating expressions across multiple languages.

Enables recurring website maintenance checks — domain registration, SSL certificates, uptime, technical SEO and accessibility — across a portfolio of client sites, using publicly available information. Results are returned as structured data and can be sorted by urgency into a client-ready report.

Enables coding agents to compile supplied files, run optional focused tests, and get static findings across ten programming languages, providing a deterministic feedback loop on the code they are about to return.

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.

Umbra is the trust layer for AI-generated code. It scores any repo 0-100 with file:line evidence (security, slop, Docker-verified build/boot, and claim receipts that catch agents lying about tests), and guards agent file writes mid-stream blocking leaked keys, alg:none JWTs, and git-hook plants before they land. Tools: scan_repo, guard_content, get_score.

Enables coding agents to drive and inspect running Shiny apps (R and Python) by setting inputs, clicking, reading outputs, and getting detailed error information.

Automated Playwright E2E test repair powered by a self-improving, governed MCP server that runs failing tests, collects failure artifacts, reasons about root causes, validates and applies fixes, and re-runs to verify.

Exposes the Maester security test framework for Microsoft 365/Entra/Defender as MCP tools, enabling AI agents to run tests, audit AI agents and MCP servers, and investigate security posture.

An MCP server that turns Zod schemas into mocks, violations, and contract tests, enabling AI agents to reason about API contracts without manually crafting payloads.

Enables AI assistants to access RenderDoc capture data and assist with graphics debugging by retrieving draw calls, shader information, buffers, textures, and pipeline state.

Turns JUnit XML test reports from CI into queryable QA metrics, letting AI assistants answer plain-English questions about failures, flaky tests, regressions pinned to a commit, root-cause clusters, and performance drift. Also generates ready-to-share QA health reports and self-contained HTML dashboards without logging into separate tools.

Rarefaction is a Model Context Protocol (MCP) server that gives a coding agent the call graph and code context for one symbol straight from the project's language server (Language Server Protocol, LSP). Ask about a function, method or type and get, in one call: its signature and doc, its body, who calls it (tests marked), what it calls, who implements it, the tests that reach it and the short list

Enables AI assistants to take measurements from a Siglent SDM3045X bench multimeter over USB or LAN, including single readings, timed samples, fast bursts, and device information. Optionally exposes raw SCPI commands for advanced instrument control.

MCP server that generates ISO/IEC/IEEE 29119-3 compliant test plan drafts from project information, providing a structured resource for the standard's test plan outline and a tool for draft creation.

Allows LLM agents to query Playwright JSON test results for run summaries and failure information.

Enables natural-language validation of IFC models against Türkiye's building-permit BIM regulation, including compliance checks, EK-9 form generation, and queries about required classes and properties.

Local MCP server for querying VCD waveform files via SQLite; enables AI agents to ask precise questions about signal values, transitions, and clock cycles without dumping raw VCD text.

Lets assistants send the same test prompts to as many as four text models across OpenRouter, Amazon Bedrock, Google Vertex AI and Microsoft Foundry, then automatically grade each answer with a judge model, rule checks and a policy gate. Returns scored leaderboards with letter grades, per-response strengths and weaknesses, latency, throughput and estimated cost, plus downloadable PDF and CSV reports.

A real security scanning MCP server for medical information systems, supporting port scanning, vulnerability detection, medical system identification, and compliance report generation.

Enables defect management on the SEPP platform, allowing users to query defects, retrieve user project information, and set up automated monitoring with alerts for new or unresolved defects via webhook or email.

Enables AI assistants to analyze and inspect RenderDoc capture files, providing tools to examine draw calls, textures, buffers, and shader information. It allows developers to perform graphics debugging and resource analysis through natural language interactions.

A lightweight, configurable server that fetches coding guidelines, security rules, and validation patterns from external sources to help development teams maintain code quality standards in WordPress projects.

An MCP router that connects to multiple PagerDuty sandbox environments for testing integrations like PD+Teams, PD+Jira, and more.

Enables an assistant to verify whether claims about AI systems hold against supplied evidence bytes, replay conformance vectors, and inspect related terms and artifact digests offline without fetching, writing, or sending data.

An MCP server that provides elicitation tools to interactively request user input, such as selecting options, providing information, or performing manual tests.

An MCP server for checking OWASP Top 10 vulnerabilities during API development testing. It analyzes API information and returns security assessment results to help developers identify potential security issues.

Provides tools to analyze test failures, cluster similar failures, and detect flaky tests from input or log files, helping QA teams debug and triage issues.

Enables agents and teams to manage versioned delivery work items, role-tagged handoffs, revision- and source-bound evidence, QA gate evaluation, and release-owner attestations through MCP tools.

Integrates with Zebrunner Test Case Management to help QA teams manage test cases, test suites, and test execution data through AI assistants. Features intelligent validation, automated test code generation, and comprehensive reporting capabilities.

Provides a portable local MCP interface for RTL simulation, diagnostics, and verification workflows with Verilator, currently exposing server information, tool discovery, and bounded text diagnostic parsing while lint and simulation execution remain planned.

Enables RTL simulation and hardware verification with Verilator through automatic testbench generation, natural language queries about simulations, waveform analysis, and protocol-aware testing for Verilog/SystemVerilog designs.

A testing server that demonstrates Model Context Protocol features, providing access to user data, todos, and system information through resources, tools for user management and calculations, and prompt templates for various analyses.

A server that converts Allure test reports into LLM-friendly formats, enabling AI models to better analyze test results and provide insights about test failures and potential fixes.

Ephemeral mailboxes and a mock OAuth IdP for testing email and auth flows — 39 API-driven tools covering mailboxes, mails, attachments, domains, teams, and mock identities.

Deterministic AST vulnerability remediation and formal verification for AI coding assistants using Microsoft Z3 SMT logic.

A frontend security dependency auditing tool that identifies vulnerabilities in local and remote repositories using the Model Context Protocol. It provides detailed audit information like CVSS scores and dependency chains, generating standardized markdown reports.

Enables AI coding agents to drive a real browser like a person — crawling every page and role, running real user journeys, and auditing controls a DOM-based test misses — so UI, accessibility and permission bugs are found and only the screens affected by recent changes are re-tested. Runs are script-driven and read-only by default, so testing costs no model tokens and nothing about the app is sent to an AI.

Enables AI clients to control and observe Candela LANforge test systems through a secure MCP gateway, supporting Wi-Fi stations, traffic, monitoring, events, alerts, automation, and more via about 40 tools plus dynamic universal access.

An MCP server that enables AI assistants to parse Xcode and Swift build outputs into structured, token-efficient formats like JSON or TOON. It provides tools for executing build commands and extracting detailed diagnostic information such as errors, warnings, and test failures.

Enables users to list and retrieve evaluation tasks, score recorded submissions, run benchmark evaluations via OpenRouter, and access provenance information through MCP tools.