A MCP server replacing REST clients like Postman/Insomnia, allowing LLMs to maintain and use API collections.
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A specialized MCP server providing LLM enhancement prompts and jailbreaks with dynamic schema adaptation, designed to augment AI capabilities via the MCP protocol.
An MCP server implementation providing endpoints for wallet-based authentication, cluster management, and name registration. Direct example of an MCP server for cluster operations.
A Model Context Protocol (MCP) server designed for dumping codebase context into LLMs, making it easier for AI models to access relevant project information. Exemplifies MCP server usage.
A Model Context Protocol server that connects LLMs to the Compiler Explorer API, enabling compilation and exploration of code across different compilers and languages. This is an MCP server providing LLMs with code analysis and compiler features.
An MCP server providing API security testing tools, including authentication and vulnerability scanning, with detailed severity ratings and remediationāillustrating security-focused MCP server capabilities.
A server implementing the MCP protocol to connect with Databricks Genie API, enabling LLMs to ask questions, execute SQL, and interact with Databricks conversational agents.
A standalone MCP server for API testing and management, designed to allow AI assistants (such as Claude) to interact with RESTful APIs through natural language. It aims to replace tools like Postman and Insomnia, with a focus on AI/LLM integration.
http_request: Send HTTP requests to any URLlist_collections: View all saved API collectionslist_requests: View all requests in a collectionsave_request: Save a request to a collectionrequest_from_collection: Execute a saved requestset_environment_variable: Set variables for request templatesget_environment_variables: View all environment variables~/.postmancer)mcp, api, postman, insomnia, llm-integration
api-integration-mcp-servers