Discover our curated collection of MCP servers for developer tools. Browse 14595servers and find the perfect MCPs for your needs.
Locates the original definitions of TypeScript symbols, including those from imported packages, within a codebase.
Provides TigerBeetle account management using the Model Context Protocol.
Provides access to Metaplex documentation and repository information through the Model Context Protocol.
Enables AI coding assistants to access and understand the React Icons library.
Provides weather forecast and alert tools via Server-Sent Events (SSE) using the Model Context Protocol (MCP).
Enables read-only access to Google Spanner data for AI clients like Claude Desktop through CData JDBC Drivers.
Provides a Model Context Protocol server for the Edgee API, enabling comprehensive management of organizations, projects, components, and user administration.
Simplifies Terraform on AWS development by providing a Dockerized Model Context Protocol (MCP) server with integrated best practices, infrastructure as code patterns, and security compliance.
Provides a modular REST API for calculating various medical scores and indices, designed for integration with large language models.
Provides an HTTP API layer to connect and query Odoo instances via XML-RPC for common tasks like retrieving leads, customers, and activities.
Accelerates the development of custom tools, resources, and prompts for AI assistants using the Model Context Protocol.
Provides multi-feature access to weather data, system utilities, Azure resources, and AI image generation/editing through the Model Context Protocol.
Analyzes .NET and Java projects for stateful code patterns, integrating with Amazon Q Developer.
Automates trade surveillance support workflows by integrating with existing SQL configurations and Java code repositories using a Model Context Protocol (MCP) server.
Empowers AI assistants to grade, generate, and validate UI components against the components.build specification using the Model Context Protocol.
Automates the setup, configuration, and lifecycle management of MCP servers for AI agents.
Enables AI agents to understand and interact with the Optics Design System's tokens, components, and documentation.
Enables AI agents to efficiently manage GitLab operations with substantial token savings.
Transforms CSV or JSON data into structured JSON outputs using declarative YAML rules with powerful expression language and DTO generation.
Empower AI assistants to autonomously build, validate, and deploy multi-agent solutions from any AI environment.
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