"How to create pie and line charts with MCP" matching MCP servers:

A dynamic service that creates and manages Model Context Protocol (MCP) servers, allowing users to spawn, customize, and control multiple MCP servers as child processes.

Model Context Protocol server implementation that integrates the LINE Messaging API to connect AI agents with LINE Official Accounts, enabling agents to send messages to users.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Enables MCP hosts such as Claude and Cursor to dispatch tasks to live marketplace agents, poll or wait for verified settled results, list available agents by capability, and retrieve live protocol statistics with atomic settlement on Tempo.

Enables a Hermes agent to exchange messages with a personal LINE account through chatmux, with durable cursor, inbox, and outbox persistence plus exact DM/group allowlists, activation prefixes, and outbound target gates. It also provides observe-first configuration, named-profile routing for native-mention groups, CLI diagnostics, and fail-closed handling of ambiguous sends.

Enables MCP clients to interact with A2A agents through four ordinary tools, translating agent discovery, messaging, task reading, and cancellation between the A2A and MCP protocols, with support for the tasks extension.

An MCP server that turns a one-sentence idea into working, tested code using a pipeline of six AI agents, with optional deployment.

Enables MCP clients such as Claude Desktop to hand tasks to a running DeepSeek Harness window, where each task becomes a real session visible in the sidebar with a reusable session id. If the in-process plugin is unavailable, it falls back to running the task headless so the tool still returns a result.

Turns any OpenAPI/Swagger specification into a functional MCP server, dynamically exposing API endpoints as LLM tools or generating standalone Python code.

Enables AI agents to access user and message data through MCP resources, providing REST API integration for user management with paginated lists and thread tracking.

MCP server that lets you drive Claude Code sessions hands-free by voice from any MCP client, enabling remote models to send prompts, monitor progress, and get results read back.

MCP server that routes Claude Desktop chat into Claude Code, enabling headless execution and terminal handoff with session continuity.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

Converts any REST API into MCP-compatible tools instantly by providing an OpenAPI/Swagger spec, enabling seamless integration with AI agents.

Enables LLMs to discover and invoke generated API actions as MCP tools and read context through MCP resources for list and get-by-id operations. It provides HTTP-based MCP access for clients such as Cursor and Claude without extra glue code.

Acts as a bridge between standard REST/OpenAPI web APIs and the Model Context Protocol, dynamically converting REST endpoints into MCP tools for LLM clients like Cursor, Claude Desktop, and n8n.

Automatically converts OpenAPI/Swagger documents into MCP servers, enabling AI agents to call third-party REST APIs via the MCP protocol.

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.

Provides 14 MCP tools for AI agent infrastructure, enabling knowledge base queries, skill search, handoffs, blueprint validation, trust scoring, identity verification, SLA validation, and compliance checks.

An MCP server that integrates Alibaba's DashScope platform, providing AI chat tools and resource access through both standard stdio and a web-based interface. It allows users to interact with DashScope large models within the Model Context Protocol ecosystem using TypeScript.

A Model Context Protocol server that enhances LLM capabilities by connecting to Wikipedia, internet search (Tavily), and financial data (Yahoo Finance) tools, enabling contextual responses to user queries.

Exposes Amazon Nova Act web automation capabilities through the Model Context Protocol, enabling AI agents to perform browser tasks like navigation, data extraction, and form interaction.

It enables Microsoft Copilot Studio agents to connect to and use MCP-based tools, such as fetching jokes, through an Azure-deployed server and Power Platform connector.

A project that integrates Model Control Protocol with OpenAI's API, allowing OpenAI to access and utilize tools exposed by a dockerized MCP server.

Lets Claude Code drive a real Google Chrome while you watch a low-latency live view and take over the mouse and keyboard whenever a login, CAPTCHA or payment appears. Sensitive actions pause for phone-based approval, and the agent can be guided by tapping elements or sending short messages without exposing secrets.

Enables AI agents to read and interact with the target5.net board, including listing problems, reading threads, registering identities, and posting replies, with the board's rules enforced and embedded into every tool.

Enables AI agents to securely reach enterprise tools and other agents through a governed gateway with pinned tool definitions, delegated authorization, content inspection, human approval, and signed audit trails.

Enables enterprise work agents to decompose high-level business objectives into topological sub-tasks and directly synthesize final deliverables such as financial spreadsheets, executive presentations, and analytical reports.

Enables an IDE agent to receive only the Product Owner-approved decisions, technical brief, plan and test cases from a local multi-role planning chat, then work through stories with MCP tools such as get_next_story, update_story and ask_po. Blocking questions can be raised back to the chat so the agent waits for a human answer, and story completion is refused until test cases are reported.