"Creating an MCP Server Using an API" matching MCP servers:

MCP server for interacting with GitLab API, supporting dynamic tool selection and enterprise-grade security.

MCP server enabling interaction with ServiceNow API for managing incidents, CMDB, change management, and other ServiceNow operations via natural language.

Signed, offline-verifiable authorization for API-contract changes. Before a contract change (OpenAPI, GraphQL, Protobuf, AsyncAPI, MCP manifests) merges or deploys, the agent calls preflight_change_set; the decision is deterministic, signed, and verifiable without calling CodeRifts. Three tools: preflight_change_set, verify_receipt, get_decision_details. Only a granted change can proceed.

Generates complete, production-ready REST, GraphQL, and microservice APIs with built-in security, validation, and deployment configurations.

Analyzes API requirements and source code, evaluates existing Postman test coverage, and generates or updates test automation with an optional draft pull request on GitHub.

Auto-generated MCP server that enables interaction with the Firebase App Distribution API, allowing users to manage distribution of pre-release app builds to testers through natural language commands.

Enables AI assistants to interact with the GitLab API, providing over 1000 tools for managing groups, projects, users, and more through natural language.

Analyzes Git pull request diffs to detect breaking REST and GraphQL API schema changes, providing deterministic AST-level code review and breaking change alerts for CI/CD workflows.

An MCP server that interfaces with the Snyk API to retrieve KPI data for your organization.

Pre-install gate for AI coding agents. Checks npm, PyPI and crates.io package names before an install runs and blocks names that do not exist, were registered after models invented them, or sit one keystroke from a popular package. CLI, GitHub Action and MCP server. Apache 2.0.

Enables AI assistants to interact with Sauce Labs testing platform through natural language, providing access to device cloud management, test job analysis, build monitoring, and testing infrastructure insights. Supports both Virtual Device Cloud (VDC) and Real Device Cloud (RDC) with comprehensive test analytics and team collaboration features.

Enables interaction with Vercel API to manage deployments, domains, projects, and environment variables.

MCP server for managing Google Play app deployment and in-app products via the Android Publisher API v3.

An MCP server for managing Modal — apps, containers, volumes, and secrets — and for deploying & running Modal apps directly from Claude Code and other MCP clients.

StorePilot is an MCP server that unifies app portfolio management across Google Play and App Store Connect, with tools for installs, earnings, reviews, cross-store parity, and gated releases.

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.

An MCP server that enables AI assistants to discover and execute Nox sessions for project automation tasks like testing, linting, and building. It provides tools to list available sessions and run them using specific Python versions, tags, or keyword expressions.

MCP server (stdio, Python standard library only) with tools would_tag, check_versions, explain_label and compare: before an agent creates a release tag, would_tag answers whether that version label already names different code in the repository's git tags. Server at integrations/mcp/closure_drift_mcp.py.

Stops your AI from re-introducing bugs, leaking provider keys, or weakening tests. Bug fixes become permanent regression guards; blocked mistakes become AI lessons the agent reads and learns from before its next edit.

Deploy, run and manage apps on your own self-hosted AppCrane from any MCP client. 62 tools: create an app, push code, deploy to sandbox, check health and logs, provision a managed Postgres, MariaDB, MongoDB or Redis, and promote to production after review. Your instance, your SSO, your data. Repo: https://github.com/gitayg/appcrane-mcp · npm: appcrane-mcp · Site: https://appcrane.dev

An MCP server that lets AI assistants manage KubeAid GitOps clusters, inspecting ArgoCD apps, pods, events, and resources, with optional write operations like syncing apps and scaling deployments through your own kubeconfig credentials.

Turns Claude Code into an interactive OpenWiFi triage assistant, providing tools for searching Linux wireless patches, Jira tickets, running LLM-based triage, backporting, and building OpenWiFi.

A Model Context Protocol server that enables AI assistants to interact with Azure DevOps services, allowing users to query work items with plans to support creating/updating items, managing pipelines, handling pull requests, and administering sprints and branch policies.

Compacts noisy test, build, and cloud-log output before an AI agent reads it — dedupes repeats, collapses stack frames, folds Playwright retries, and renders CloudWatch/GCP JSON logs down to the signal. Typically 80–95% fewer tokens on failures. Tool: compact_output. Run: npx -y logslim logslim-mcp

An MCP server that provides deterministic tools for AI assistants to standardize development workflows, including branch naming, commit validation, and PR checklists.

An MCP server that scaffolds full-stack projects with consistent structure, Docker setup, CI/CD pipelines, and database configuration.

MCP server that triggers Jenkins automation jobs and returns their results, with an action registry, parameter validation, and credential redaction.

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 enables AI assistants to interact with Apache Airflow's REST API for DAG management, task monitoring, and system diagnostics. It provides comprehensive tools for triggering workflows, retrieving logs, and inspecting system health across Airflow 2.x and 3.x versions.

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.