"Managing and searching Jira ticket creation" matching MCP servers:

A Model Context Protocol (MCP) server that enables interaction with JIRA APIs through Claude Desktop, allowing users to search, create, update, and manage JIRA issues using natural language commands.

Enables LLMs to interact directly with generated REST APIs by exposing CRUD actions as MCP tools and read-only data as MCP resources.

Enables LLMs to discover and use generated REST API services as Model Context Protocol tools and resources, supporting CRUD actions and read-only data access without custom glue code.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

Lets AI assistants safely explore a Matrix42 instance by discovering web services and the data model, running validated ASQL queries, searching the service desk, and previewing ticket actions — read-only by default and without exposing credentials.

Enables AI assistants to query API documentation from Eolink Apikit instances via the Eolink Open API, supporting listing projects, groups, searching APIs by keyword/path, and retrieving detailed API definitions.

Enables AI assistants to explore and interact with the Facets Control Plane API via natural language, supporting operations like searching endpoints, loading schemas, and making authenticated API calls.

A read-only MCP server that exposes Automeli's public API documentation (v2 canonical, v1 frozen) to LLMs via fetch and cache over www.automeli.com artifacts. It enables listing, searching, and retrieving endpoints, OpenAPI specs, error explanations, code snippets, and end-to-end flow guides.

Enables AI agents to create, run, and manage HTTP requests using the Invoker API client's .ivk format. It provides tools for scanning collections, executing requests, managing environments, and building documentation sites.

A high-performance, multi-protocol API mock server with 18 built-in MCP tools for managing HTTP, GraphQL, gRPC, WebSocket, MQTT, SSE, and SOAP mocks, chaos engineering, stateful CRUD resources, and request verification.

Exposes YApi's API management capabilities to MCP clients, enabling operations like listing projects, categories, searching APIs, and managing API details.

Zero-telemetry local developer execution layer for AI coding agents. Provides deterministic tools to inspect listening network ports and processes, calculate IPv4 CIDR subnet ranges and usable hosts, decode embedded creation timestamps from distributed IDs (UUIDv7, ULID, Snowflake, MongoDB ObjectId), and convert Unix epoch timestamps to UTC, ISO 8601, and local time.

Enables searching YApi interfaces by keyword and retrieving detailed interface schemas, including request/response, for project-level tokens.

Provides OpenAPI validation and analysis tools to assist developers in building Model Context Protocol servers. It generates developer context and specific agent prompts based on API specifications to streamline the creation of agentic workflows.

Read-only MCP server for indexing and searching Bruno API collections. Enables endpoint discovery and contract retrieval without executing requests.

A lightweight MCP server for searching SmugMug documentation and calling the live SmugMug API.

MCP server for managing Apidog test cases, scenarios, suites, and test data, providing full read/write access to Apidog's test management features.

A lightweight, local-first MCP server for executing HTTP requests and managing API collections and environments without cloud dependencies. It enables testing APIs, handling authentication, and importing OpenAPI specifications directly within MCP-compatible workflows.

Enables searching and reading published Hoppscotch API documentation, inspecting endpoint details, and retrieving saved response examples through MCP tools.

Enables AI agents to read realistic, coherent data—repos, pull requests, issues, commits, users—through API-compatible, read-only replicas of 21 developer platforms including GitHub, Jira, Linear, Slack, Sentry and Salesforce, all preloaded with one simulated company so integrations can be built and tested with no accounts, credentials, rate-limit worry, or cleanup.

Exposes the Hookbase webhook relay API as tools for AI assistants to manage sources, destinations, routes, and events through natural language. It enables monitoring webhook success rates, replaying failed deliveries, and managing localhost tunnels for development.

Enables AI assistants to manage API endpoints, environments, and testing workflows through the GASSAPI backend. Provides semantic documentation tools for endpoint cataloging and automated flow creation for backend-to-frontend development workflows.

Enables MCP clients to manage YApi projects and interfaces, including searching and creating APIs, editing mock response bodies and advanced mock scripts, managing mock expectations, and testing mock URLs.

Monitors API endpoint health by checking availability, measuring response times, and providing detailed status reports with error handling and timeout protection for the localhost:8080/api/ticket endpoint.

Enables AI assistants to interact with TestRail test management systems through comprehensive API integration. Supports retrieving and updating test cases, projects, suites, runs, and results, plus adding attachments and managing test data through natural language commands.

Exposes ProxyPin's local network capture history to MCP-capable clients for searching, analyzing, and detailing captured HTTP traffic. It enables users to perform API structure analysis and generate client-side code directly from captured requests.

Enables AI tools to create and manage API requests and collections in Thunder Client, with automated collection and folder creation.

An MCP server that integrates the Neople Cyphers Open API with AI assistants for searching players, match histories, and rankings. It provides tools for retrieving character info, game items, and real-time statistics directly through natural language.