MCP server directory

> [!WARNING] > This local MCP server is deprecated in favor of the ElevenLabs hosted MCP server. > > The hosted server is available at https://api.elevenlabs.io/v1/mcp, with nothing to install or run locally. It authenticates with OAuth, so no API keys are copied into your client. See the hosted MCP server documentation to connect from Claude, Cursor, or any other MCP client. > > This repository is no longer actively maintained. 1. Get your API key from ElevenLabs. There is a free tier with 10k credits per month. 2. Install uv (Python package manager), install with curl -LsSf https://astral.sh/uv/install.sh | sh or see the uv repo for additional install methods. 3. Go to Claude > Settings > Developer > Edit Config > claude_desktop_config.json to include the following:

6 tools · isolate_audio, sound_effects

Run MATLAB® using AI applications with the official MATLAB MCP Server from MathWorks®. The MATLAB MCP Server allows your AI applications to: - Start and quit MATLAB. - Write and run MATLAB code. - Assess your MATLAB code for style and correctness. To assist your agent in using MATLAB and Simulink, you can use skills from MATLAB Agentic Toolkit (GitHub) and Simulink Agentic Toolkit (GitHub), which can also install this MCP server for you. - Setup - Claude Code - Claude Desktop - GitHub Copilot in Visual Studio Code - Codex - Arguments - Tools - Resources - Data Collection - Security Considerations - Licensing and Usage - Contact Support

5 tools · check_matlab_code, detect_matlab_toolboxes

A ModelContextProtocol server that gives your AI coding tool or agent access to documentation for APIs, services, libraries etc. It's your one-stop-shop to keep your agent up-to-date on documentation in a fast and token-efficient way. Ref's tools are designed to match how models search while using as little context as possible to reduce context rot. The goal is to find exactly the context your coding agent needs to be successful while using minimum tokens. Depending on the complexity of the prompt, LLM coding agents like Claude Code will typically do one or more searches and then choose a few resources to read in more depth.

4 tools · Get token-efficient context, ref_read_url

The official Atlassian Rovo MCP Server is a cloud-based bridge between your Atlassian Cloud site and compatible external tools. Once configured, it enables those tools to interact with Jira, Confluence, Jira Service Management, Bitbucket, and Compass data in real time. Authentication uses OAuth 2.1 or API tokens, so every action respects the user's existing access controls. With the Atlassian Rovo MCP Server, you can: Summarize and search Jira, Confluence, Jira Service Management, and Bitbucket content without switching tools. Create and update issues or pages based on natural language commands. Automate repetitive work, like generating tickets from meeting notes or specs.

6 tools · Bulk issue creation, Create and update work items

This repository is no longer maintained. The core functionality has been integrated into all IntelliJ-based IDEs since version 2025.2. The built-in functionality works with SSE and JVM-based proxy (for STDIO) so this NPM package is no longer required. Migration: Please refer to the official documentation for details on using the built-in functionality. Issues & Support: For bugs or feature requests related to the built-in MCP functionality, please use the JetBrains YouTrack%7D%20). The server proxies requests from client to JetBrains IDE.

3 tools · Configure which IDE instance to target, Connect your AI assistant to a running JetBrains IDE

The gcloud Model Context Protocol (MCP) server enables AI assistants to easily interact with the Google Cloud environment using the gcloud CLI. With the gcloud MCP server you can: - Interact with Google Cloud using natural language. Describe the outcome you want instead of memorizing complex command syntax, flags, and arguments. - Automate and simplify complex workflows. Chain multiple cloud operations into a single, repeatable command to reduce manual effort and the chance of error. - Lower the barrier to entry for cloud management. Empower team members who are less familiar with gcloud to perform powerful actions confidently and safely.

5 tools · execute_insights_query, gcloud

This is Hyperbrowser's Model Context Protocol (MCP) Server. It provides various tools to scrape, extract structured data, and crawl webpages. It also provides easy access to general purpose browser agents like OpenAI's CUA, Anthropic's Claude Computer Use, and Browser Use. More information about the Hyperbrowser can be found here. The hyperbrowser API supports a superset of features present in the mcp server. More information about the Model Context Protocol can be found here. - Installation - Usage - Tools - Configuration - License

6 tools · browser_use_agent, crawl_webpages

Search issues, update statuses, and sync project work from Linear.

2 tools · search_issues, update_issue

https://github.com/user-attachments/assets/eeb9c4cb-c80d-42da-bf63-c0c4ecb1e5d6 Every AI coding agent today — Cursor, Claude Code, Cline, Copilot — works the same way: 1. You type a prompt 2. Agent immediately starts writing code 3. You have zero visibility into what it's doing 4. You realize it misunderstood your request 5. Hundreds of lines of code need to be discarded 6. You've wasted tokens, time, and patience Some agents show plans as text in chat. But text fails to show: - Dependencies — which tasks depend on what? - Branch points — what alternative approaches exist? - Context requirements — which files, APIs, or secrets are needed? - Complexity — which steps are risky? - Progress — what's done, what's next?

5 tools · check_pause, get_resume_info

The SonarQube MCP Server is a Model Context Protocol (MCP) server that enables seamless integration with SonarQube Server or Cloud for code quality and security. It also supports the analysis of code snippet directly within the agent context. > 🔒 Important: Your SonarQube token is a sensitive credential. Follow these security practices: When using CLI commands: - Avoid hardcoding tokens in command-line arguments – they get saved in shell history - Use environment variables – set tokens in environment variables before running commands

5 tools · analyze_code_snippet, Check quality gates

Enable MCP-compatible AI agents to deploy apps to Cloud Run. Deploy from Gemini CLI and other AI-powered CLI agents: Deploy from agent SDKs, like the Google Gen AI SDK or Agent Development Kit. > [!NOTE] > This is the repository of an MCP server to deploy code to Cloud Run, to learn how to host MCP servers on Cloud Run, visit the Cloud Run documentation. - deploy-file-contents: Deploys files to Cloud Run by providing their contents directly. - list-services: Lists Cloud Run services in a given project and region. - get-service: Gets details for a specific Cloud Run service. - get-service-log: Gets Logs and Error Messages for a specific Cloud Run service.

5 tools · deploy, Deploy code directly to Cloud Run

AI coding agents waste tokens exploring codebases. Every grep, glob, and file read costs money. On complex tasks, agents spawn multiple Explore sub-agents that scan hundreds of files just to build context. tokensave gives agents a pre-indexed semantic knowledge graph. Instead of scanning files, the agent queries the graph and gets instant, structured answers -- the right symbols, their relationships, and source code, in one call. Without tokensave: Agents use grep, glob, and Read to scan files -- many API calls, high token usage.

6 tools · login, tokensave_branch_search

Connect your AI agent to the Resend platform. Send and receive emails, manage contacts, broadcasts, domains, and more, directly from any MCP client like Claude, Cursor, or Claude Code. We offer both a remote MCP server hosted by Resend and a local MCP server (this package). Connect any MCP client that supports remote servers (Streamable HTTP). There's nothing to install and no local process to run, which makes it the best option for web-based clients like Claude and hosted agent platforms. When you connect, your client opens a browser window to log in to Resend and approve access using OAuth.

6 tools · add_suppressions, create_contact

Library for connecting AI agents to Todoist. Includes tools that can be integrated into LLMs, enabling them to access and modify a Todoist account on the user's behalf. These tools can be used both through an MCP server, or imported directly in other projects to integrate them to your own AI conversational interfaces. Here's an example using Vercel's AI SDK. // Create Todoist API client const client = new TodoistApi(process.env.TODOIST_API_KEY) // Helper to wrap tools with the client function wrapTool(tool, todoistClient) { return { ...tool, execute(args) { return tool.execute(args, todoistClient) }, } }

4 tools · Add new tasks, Check account identity

Connect AI assistants to your data using DuckDB's powerful analytical SQL engine. Supports connecting to local DuckDB files, in-memory databases, S3-hosted databases, and MotherDuck. Allows executing SQL read- and write-queries, browsing database catalogs, and switching between different database connections on-the-fly. Looking for a fully-managed remote MCP server for MotherDuck? → Go to the MotherDuck Remote MCP docs > 📝 Migrating from v0.x? > - Read-only by default: The server now runs in read-only mode by default. Add --read-write to enable write access. See Securing for Production. > - Default database changed: --db-path default changed from md: to :memory:. Add --db-path md: explicitly for MotherDuck. > - MotherDuck read-only requires read-scaling token: MotherDuck connections in read-only mode require a read-scaling token. Regular tokens require --read-write.

5 tools · Connect to MotherDuck for cloud analytics, Control query output size

Deploy apps and provision cloud infrastructure from scratch on AWS, Azure, GCP, DigitalOcean, and Hetzner: in accounts you control. One platform to replace many tools: Terraform + Ansible + Jenkins + PaaS (Vercel, Heroku, etc), and stack-specific server panels. Manage apps, Linux servers, and cloud infrastructure from anywhere: web, mobile, API, or natural language in your AI agent through MCP. No SSH or cloud console for routine work. Ask your AI agent to provision servers, deploy apps, migrate between clouds, and manage infrastructure through one MCP server: not a separate integration per cloud or stack.

4 tools · Deploy applications, Manage role-based permissions

> Deprecated: This project is no longer actively maintained. It may not receive further updates or bug fixes. This repository contains the source code for the E2B MCP server. The E2B MCP server allows you to add code interpreting capabilities to your Claude Desktop app via the E2B Sandbox. See demo here. You can also install E2B for Claude Desktop automatically via Smithery:

3 tools · Analyze data with code interpreter, Execute code in a secure sandbox

Model Context Protocol server for automating Firefox via WebDriver BiDi (through Selenium WebDriver). Works with Claude Code, Claude Desktop, Cursor, Cline and other MCP clients. Repository: https://github.com/mozilla/firefox-devtools-mcp > Note: This MCP server requires a local Firefox browser installation and cannot run on cloud hosting services like glama.ai. Use npx @mozilla/firefox-devtools-mcp@latest to run locally, or use Docker with the provided Dockerfile. Browser MCP servers carry inherent risks. A few key practices:

6 tools · evaluate_script, get_firefox_info

Node.js server implementing Model Context Protocol (MCP) for Mapbox APIs. The Mapbox MCP Server transforms any AI agent or application into a geospatially-aware system by providing seamless access to Mapbox's comprehensive location intelligence platform. With this server, your AI can understand and reason about places, navigate the physical world, and access rich geospatial data including: - Global geocoding to convert addresses and place names to coordinates and vice versa - Points of interest (POI) search across millions of businesses, landmarks, and places worldwide - Multi-modal routing for driving, walking, and cycling with real-time traffic - Travel time matrices to analyze accessibility and optimize logistics - Route optimization to find the optimal visiting order for multiple stops (traveling salesman problem) - Map matching to snap GPS traces to the road network for clean route visualization - Isochrone generation to visualize areas reachable within specific time or distance c

6 tools · directions_tool, distance_tool

http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. --> Apache Doris MCP Server exposes read-only Apache Doris capabilities to MCP Hosts and AI agents over MCP 2026-07-28. Version 1.0 replaces a large flat tool surface with eight stable domains and fifty-five progressively disclosed child capabilities, while keeping runtime availability, authorization, input schemas, output schemas, and failure behavior explicit.

6 tools · doris_catalog, doris_cluster

Repo for the official Svelte MCP server. 1. Set the VOYAGE_API_KEY for embeddings support > [!NOTE] > Currently to prevent having a bunch of Timeout logs on vercel we shut down the SSE channel immediately. This means that we can't use server.log and we are not sending list-changed notifications. We can use elicitation and sampling since those are sent on the same stream of the POST request - Transport type: Streamable HTTP - http://localhost:5173/mcp

3 tools · ask_svelte, get_examples

The Postman MCP Server implements the Model Context Protocol (MCP) to connect AI agents and coding assistants — including Claude Code, Cursor, VS Code Copilot, GitHub Copilot CLI, and Gemini CLI — directly to your Postman workspaces, collections, specifications, and environments. Postman also offers the server as an npm package. For the full installation guide with agent-specific setup, see Postman's MCP Server product page. The Postman MCP Server collection is the quickest way to explore, test, and connect to the Postman MCP Server. Use it to:

5 tools · Create specs from code, Generate client code

A Model Context Protocol server for Plane. Gives an AI agent tools to read and manage projects, work items, cycles, modules, releases, customers and more. Built on FastMCP and the official plane-sdk. - 30 tools, one per Plane resource, covering 204 operations - Local or remote — stdio, streamable HTTP, SSE - OAuth or API key authentication Get an API key from Plane: Workspace Settings → API tokens. Add this to your MCP client's configuration: uvx needs no install step. Requires Python 3.10+. For a self-hosted Plane, add "PLANE_BASE_URL": "https://plane.example.com".

5 tools · Create and manage work items, get_pql_reference

MCP Server for ForeverVM, enabling Claude to execute code in a Python REPL. - Create a Python REPL. - Returns: ID of the new REPL. 2. run-python-in-repl - Execute code in a Python REPL. - Required Inputs: - code (string): code that the Python REPL will run. - replId (string): ID of the REPL to run the code on. - Returns: Result of the code executed. In the MCP client, set the command to npm and the arguments to:

3 tools · Chain multiple code executions in one session, Run Python code in an existing REPL

The Meilisearch MCP Server is a Model Context Protocol server that enables any MCP-compatible client (including Claude, OpenAI agents, and other LLMs) to interact with Meilisearch. This stdio-based server allows AI assistants to manage search indices, perform searches, and handle your data through natural conversation. Why use this? - 🤖 Universal Compatibility - Works with any MCP client, not just Claude - 🗣️ Natural Language Control - Manage Meilisearch through conversation with any LLM - 🚀 Zero Learning Curve - No need to learn Meilisearch's API - 🔧 Full Feature Access - All Meilisearch capabilities at your fingertips - 🔄 Dynamic Connections - Switch between Meilisearch instances on the fly - 📡 stdio Transport - Currently uses stdio; native Meilisearch MCP support coming soon!

5 tools · Add and retrieve documents, Create and manage indices

The PayPal Agent Toolkit enables popular agent frameworks including OpenAI's Agent SDK, LangChain, Vercel's AI SDK, and Model Context Protocol (MCP) to integrate with PayPal APIs through function calling. It includes support for TypeScript and is built on top of PayPal APIs and the PayPal SDKs. The PayPal Agent toolkit provides the following tools: - create_invoice: Create a new invoice in the PayPal system, including recipient billing details, line items, an invoice note, a custom color theme, an optional shipping cost, and an option to enable PAY_BY_BANK as a payment method - list_invoices: List invoices with optional pagination and filtering - get_invoice: Retrieve details of a specific invoice - send_invoice: Send an invoice to recipients - send_invoice_reminder: Send a reminder for an existing invoice - cancel_sent_invoice: Cancel a sent invoice - generate_invoice_qr_code: Generate a QR code for an invoice - delete_invoice: Permanently delete a draft or scheduled invoice - generat

6 tools · create_invoice, create_order

The StarRocks MCP Server acts as a bridge between AI assistants and StarRocks databases. It allows for direct SQL execution, database exploration, data visualization via charts, and retrieving detailed schema/data overviews without requiring complex client-side setup. - Direct SQL Execution: Run SELECT queries (read_query) and DDL/DML commands (write_query). - Database Exploration: List databases and tables, retrieve table schemas (starrocks:// resources). - System Information: Access internal StarRocks metrics and states via the proc:// resource path. - Detailed Overviews: Get comprehensive summaries of tables (table_overview) or entire databases (db_overview), including column definitions, row counts, and sample data. - Data Visualization: Execute a query and generate a Plotly chart directly from the results (query_and_plotly_chart). - Intelligent Caching: Table and database overviews are cached in memory to speed up repeated requests. Cache can be bypassed when needed. - Flexible Co

6 tools · Explore database schemas, query_and_plotly_chart

MCP (Model Context Protocol) is an open standard that lets AI assistants (ChatGPT, Claude, VS Code Copilot, JetBrains AI, Codex, and others) use external tools. This server exposes the entire Zabbix API as MCP tools — allowing any compatible AI assistant to query hosts, check problems, manage templates, acknowledge events, and perform any other Zabbix operation. The server runs as a standalone HTTP service. AI clients connect to it over the network. - Complete API coverage - All 58 Zabbix API groups (223 tools): hosts, problems, triggers, templates, users, dashboards, and more - Extension tools (14) - Pre-correlated views: host_status_get, hostgroup_overview_get, infrastructure_summary_get, item_history_summary_get, problem_active_get (fold 3-5 raw API calls into one round-trip). Plus graph_render (PNG export), anomaly_detect (z-score analysis), capacity_forecast (linear regression), item_threshold_search (filter items by lastvalue thresholds), report_generate (PDF reports), action_pre

6 tools · action_prepare, anomaly_detect

> The blazing-fast, privacy-first MCP server for deep code intelligence A Rust-powered MCP (Model Context Protocol) server providing AI assistants with deep code understanding through 90 specialized tools. - Code Intelligence - Symbol extraction, semantic search, call graph analysis - Neural Semantic Search - Find similar code using embeddings (Voyage AI, OpenAI) - Security Analysis - Taint analysis, vulnerability scanning, OWASP/CWE coverage - Supply Chain Security - SBOM generation, dependency auditing, license compliance - Advanced Analysis - Control flow graphs, data flow analysis, dead code detection

6 tools · find_symbols, generate_sbom

An mcp server for your food ordering needs. - 🔎 Restaurant Discovery - Find nearby restaurants based on your location and preferences. - 📒 Menu Browsing - Browse through detailed menus with prices, descriptions, and ratings. - 🛒 Cart Creation - Add items to your cart and customize orders with ease. - 🥗 Food Ordering - Place orders seamlessly with order tracking support. - 💳 QR code payment - Complete secure payments using QR code integration. Your space to build AI agents, integrations, and personal-use apps on top of Zomato MCP. To request access (for personal use only), fill out the form, and we'll review your request.

5 tools · add_to_cart, generate_payment_qr

Real-time progress updates can be viewed on page Real-time progress For support on the x402 protocol, please click here Zen7 Payment Agent is the first practical implementation of DePA (Decentralized Payment Agent), pioneering the next generation of intelligent payment infrastructure. It not only fully implements the core functionalities of DePA but also successfully deploys innovative application cases in the agentic commerce domain. As the first practical project in the DePA ecosystem, Zen7 implements several key features: automated encrypted payments between agents, a "permissionless authorization" mechanism, and LLM-driven intent recognition and interaction.

4 tools · allowance_agent, payer_agent

> The Workspace MCP (@taskade/mcp-server) — run your Taskade workspace from any AI client. Connect Taskade to any AI assistant — Claude, Cursor, Windsurf, VS Code, and more — via the Model Context Protocol. 62 tools for workspaces, projects, tasks, AI agents, agent chat, webhooks, knowledge bases, templates, media, and sharing — all from your AI client. - MCP Server — Connect Taskade to Claude Desktop, Cursor, Windsurf, or any MCP client. - OpenAPI Codegen — Generate MCP tools from any OpenAPI spec — not just Taskade.

6 tools · Automate project creation from templates, Build and deploy AI agents

AlibabaCloud Devops MCP Server provides AI assistants with the ability to interact with the Yunxiao platform, enabling them to read work item contents in projects, automatically write code after understanding requirements, and submit code merge requests. Enterprise development teams can use it to assist with code reviews, optimize task management, reduce repetitive operations, and thus focus on more important innovation and product delivery. alibabacloud-devops-mcp-server provides the following capabilities for AI assistants:

6 tools · execute_app_release_stage, get_organization_departments

> A no-signup, no-KYC crypto payment gateway with card-to-crypto checkout — your AI agent can deploy and operate it over MCP. > Hosted endpoint: https://mcp.payram.com/mcp · Website · Docs · Agentic · OpenClaw An MCP (Model Context Protocol) server that lets any MCP-aware AI agent — OpenClaw, Hermes, Claude, Cursor, GitHub Copilot, and others — deploy, integrate, and operate a self-hosted PayRam crypto-payment stack. It exposes tools to assess a codebase, scaffold starter apps, generate multi-language integration snippets, read inline docs, create payment links, and check node sync + payment readiness against your own deployment.

6 tools · assess_payram_project, check_payment_readiness