"How to fill out a webpage form" matching MCP servers:

. A good description should be concise and describe what the server enables users to do, e.g. * Enables to interact with WordPress sites...' Then a huge block? Actually the user message includes the README content inside tags, then after the readme, there is a large block of text starting with '{

A secure, containerized MCP server that enables AI assistants to manage Terraform infrastructure using integrated Language Server Protocol (LSP) tools. It facilitates safe operations like initialization, validation, and planning while providing context-aware code completion and documentation.

Enables AI assistants to summarize Playwright test runs, identify flaky tests, heuristically triage failures, generate Playwright test stubs, and retrieve recent GitHub CI status through MCP tool calls.

Enables scanning Python repos for dead code and automatically drafting a branch + PR for the safe subset (unused single-name imports) after running the repo's full test suite. All other findings are reported without modification, and a human always merges.

Automates the full setup and deployment of Ballerina + Apache ActiveMQ integrations inside a WSO2 Integrator workspace, from broker validation to a runnable BI-low-code-ready project.

Record an agent's MCP tool-call workflow once, replay it deterministically for zero tokens, and get a receipt — a snapshot-testing and deterministic-execution layer for Agent Skills.

A Model Context Protocol server that monitors shadow-cljs builds and provides real-time build status updates for ClojureScript projects, allowing LLMs to verify build status after making code changes.

Enables AI agents to deploy, manage, and configure web applications on sota.io, including project creation, deployment, environment variables, custom domains, and rollbacks.

Enables AI coding agents to see their Odoo.sh projects by listing projects, branches and builds, waiting for a build to finish, reading build and server logs, and optionally rebuilding branches or updating the firewall. It runs read-only by default with bounded, time-limited tool calls, keeping the user's Odoo.sh session out of the agent's reach.

Publishes normalized release notices to a configured webhook via MCP, with built-in validation, deterministic dry-run mode, and a clear boundary for authority gates.

Publishes what an AI made — a page, a markdown or PDF doc, or a whole site — to a live HTTPS link. Runs locally over stdio from the @drop2run/mcp npm package, or hosted at https://mcp.dropto.run/mcp for chats that connect by URL.

An MCP server that enforces disciplined Git workflows by planning coding tasks into small, test-gated commits, ensuring tests pass before staging and preventing out-of-scope or oversized changes.

Enables AI assistants to interact with TrafficMorph for load-testing and CI-failure triage, including run management, profile lifecycle, and domain verification through natural language.

Converts Jenkins declarative pipelines into GitHub Actions workflow YAML files, facilitating migration from Jenkins to GitHub Actions CI/CD.

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.

AI Gateway - MCP server providing AI-powered tools and automation by MEOK AI Labs

Checks how long ago a package version was published and returns the newest version older than a minimum age (3 days by default), so an agent avoids brand new releases when adding dependencies. Also checks lockfiles across 15 ecosystems; read-only.

Enables agents to deploy software via GitHub Actions only with a signed receipt, providing gated tools to resolve refs, list deployments/environments, and dispatch pipelines for a specific commit.

Generates comprehensive API test plans (positive, negative, and boundary cases) from endpoint metadata and exports them as Excel files.

MCP server that connects AI agents to Jenkins, supporting stdio and HTTP transports with tools for jobs, builds, logs, and queue management.

Enables AI assistants to manage Bitbucket Cloud repositories, pull requests, branches, commits, pipelines, issues, and webhooks through the Model Context Protocol.

Checks the outcome after an agent handoff, when a request, 200 or ack only shows the handoff. Reads one field of one exact public HTTPS JSON record, with a same-site known-good control, for 20-120 s. Returns PROVED, DISPROVED or INCONCLUSIVE with a signed receipt you can verify. 5 free checks, then USD 1 per completed check, by card (Stripe Checkout) or existing Link wallet. INCONCLUSIVE is free.

A specialized MCP server for QA engineering. It provides tools for user story analysis, test strategy, BDD/Gherkin scenarios, contract testing, integration tests, performance plans, security checklists, and CI/CD pipeline generation, accessible from any MCP-compatible IDE or client.

Enables Claude to interact with R package development workflows, including CRAN metadata lookup, dependency checking, testing, documentation validation, and release automation.

A demonstration MCP server built with FastMCP v2.0 that provides basic mathematical calculations and greeting functionality. Features Docker containerization, comprehensive testing, and CI/CD automation for learning MCP development patterns.

Forces every AI Agent code change (Claude Code, Cursor, Trae) to leave a structured problem/reason/approach audit record before commit. 11 MCP tools with full annotations, pre-commit hook blocks unaudited changes. Local stdio, no API key, MIT. M8ven Trust 100/A.

Enables LLM clients to access DevSecOps tooling such as CI/CD pipeline status, vulnerability triage, log search, and dependency scanning through MCP, turning AI copilots into security-aware engineering partners.

Enables AI clients to analyze software test results and defect records, producing explainable GO, CONDITIONAL_GO, or NO_GO release-readiness recommendations with deterministic risk scoring, failed-test retrieval, defect hotspot ranking, and regression test planning.

Enables intelligent access to AL-Go documentation, workflows, and domain expertise for Business Central development automation through specialized personas and cross-source semantic search.

Enables searching, reading, and analyzing discussions on GitLab's community forum for troubleshooting CI/CD issues and GitLab features. Pre-configured with GitLab-specific search filters and optimized workflows for support scenarios.