"Information or services related to GHL" matching MCP servers:

A production-grade MCP server that wraps the GoHighLevel API v2, enabling Claude and other MCP clients to interact with GHL CRM as structured tools for managing contacts, conversations, pipelines, appointments, payments, and more.

Provides AI assistants with access to all public GoHighLevel API endpoints as MCP tools, enabling contact, conversation, opportunity, calendar, and other CRM operations with configurable safety gates for writes and deletes.

Enables comprehensive search and browsing of Berlin city services. Also supports PDF form discovery, analysis, and filling with resilient caching.

An MCP server for GoHighLevel with 82 live-tested tools, enabling CRM operations like contact management, appointments, invoices, and workflows via natural language.

Enables Claude to manage GoHighLevel CRM contacts, pipelines, and workflows through natural language commands.

Enables interaction with the Swipe Saver Pro GHL location for managing contacts, custom fields, tags, opportunities, and pipelines via the GoHighLevel API.

Provides MCP tools to interact with GoHighLevel CRM data, including contacts, conversations, call transcripts, broker lead overviews, pipelines/opportunities, and task creation. Supports both stdio and HTTP transports for local and remote use.

A Model Context Protocol server that converts Markdown documents to plain text with flexible options and dual protocol support.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

Converts any Python Click or Typer CLI into an MCP server automatically — zero-code transformation that introspects CLI commands and exposes them as MCP tools.

Enables existing Express routers to be exposed as MCP tools, dispatching tool calls through the Express middleware stack in-process without a network hop.

A standalone proxy that transforms any OpenAPI or Swagger-described REST API into an MCP server by mapping API operations to executable MCP tools. It enables AI clients to interact with existing web services through automated HTTP requests based on their official documentation.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Automatically converts Swagger/OpenAPI specifications into dynamic MCP tools, enabling interaction with any REST API through natural language by loading specs from local files or URLs.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

Converts natural language queries into valid GraphQL queries and executes them against GraphQL APIs. Includes schema introspection, query validation, execution with authentication, and query history tracking.

An MCP server that enables AI agents to retrieve detailed GitHub Pull Request information using git commit hashes, branch names, or PR numbers. It automatically detects repositories and extracts comprehensive PR data including descriptions, labels, and reviews via the GitHub CLI.

One-pass agentic inbox triage as an MCP server: fetch unread Gmail → classify (action_needed/fyi/newsletter/noise) → summarize → extract tasks → draft replies as Gmail DRAFTS (never sends) → flag calendar → write a triage report. Four stdio tools (fetch_emails, save_gmail_draft, append_tasks, write_report); the host is the LLM, so it runs keyless in Claude Code. Gmail scopes: readonly + compose

Converts JSON data to TOON (Token-Oriented Object Notation) format and back, reducing token usage by 30-60% for more efficient LLM applications.