Highlevel MCP

I've been building AI-powered client systems on GoHighLevel for two years and I'm a strong advocate for the platform. I recently integrated Claude AI via your MCP server and the potential is genuinely game-changing — but the current MCP implementation has critical gaps that are preventing true AI-powered automation of GHL. Here's what's missing that would unlock full AI-driven system building: Pipeline creation and stage management via API Workflow/automation builder access — create triggers, actions, and full workflows Funnel and page builder write access Custom field and folder creation with full picklist support Tag creation and management Email template creation and sequence building Snapshot creation and deployment Sub-account creation and configuration Form and survey builder access Right now I can read CRM data via MCP but I have to manually build pipelines, automations, funnels, and templates by hand or resort to raw Terminal API scripts. The vision of an AI agent that can build an entire client system end-to-end — pipelines, workflows, funnels, automations, all of it — is completely achievable on your platform, but only if these write endpoints are exposed in the MCP. Your roadmap mentions expanding to 250+ tools. I'd strongly urge you to prioritize the workflow builder and pipeline creation endpoints first — those two alone would transform how agencies deliver client work on GHL. The agencies that figure this out first will have an insurmountable competitive advantage. GHL has the opportunity to be the platform that makes that possible. I'd love to connect and share more about what we're building at LeadVortex AI.

Agent ready HighLevel MCP for Codex, Claude, ChatGPT, and other AI builders Details HighLevel should release an official agent ready MCP that lets tools like Codex, Claude, ChatGPT, Cursor, and local AI agents safely connect to sub accounts and build inside HighLevel. The MVP should cover the core actions agencies need every day: Read, create, update, and search contacts Read, create, update, and search opportunities Read and send conversations Read and create calendar appointments Read and update custom fields Read and trigger workflows Read locations and sub account settings Access forms, funnels, websites, calendars, pipelines, tags, users, and snapshots Use strict permissions so agents only touch the connected location Include clear docs, examples, sandbox mode, and audit logs This would let agencies build client systems faster, troubleshoot accounts, create workflows, set up AI employees, and manage sub accounts without relying on fragile browser automation. The big win is simple: HighLevel becomes the operating system AI agents can actually build on.

THE PROBLEM The MCP server now exposes get-message-recording, wrapping GET /conversations/messages/{messageId}/locations/{locationId}/recording. It returns HTTP 200 and real audio. But the audio arrives unusable. The operation registry declares this endpoint as: responseContentTypes: ["application/json"] That is wrong. The endpoint returns audio/x-wav. Because the executor believes the response is text, it decodes the body as UTF-8 before putting it in the data field. Every byte that is not valid UTF-8 becomes U+FFFD, the replacement character. MEASURED ON A REAL 26 SECOND CALL data is a str of 394220 chars U+FFFD count: 205969 (52.2% of payload) non-ASCII bytes that survived: 17 52.2 percent of the audio is replaced by one repeated codepoint. Only 17 high bytes survived, the ones that happened to form valid UTF-8 sequences by chance. This is a lossy decode, not base64, so no client-side decoding recovers it. Many distinct original bytes all collapse to the same U+FFFD. The damage reaches the header. A WAV begins with "RIFF" plus a 4 byte little-endian size field: 0x52 0x49 0x46 0x46 R I F F 0xFFFD 0x06 0x06 0x00 <- first size byte already replaced So it is not a corrupt-but-salvageable file. The length field itself is unreadable. WHY THIS MATTERS We run a managed follow-up audit service across agency sub-accounts. HighLevel's own transcription covers most calls, and get-message-transcription over MCP works perfectly. We verified it is byte-identical to the REST response: rendered through our own pipeline, both produce the same 1404 characters, same speaker indices, same sentence splits. That tool is excellent. The gap is the remainder. Roughly 8 percent of calls in our pilot account have no HighLevel transcript, and those need the recording so we can transcribe locally. That one path forces us to keep a separate Private Integration Token and a parallel REST client purely to fetch audio the MCP already reaches but mangles. THE FIX (any one of these works) Option A: Correct the content type in the operation registry so the executor stops decoding binary as text, and return the audio base64 encoded. Option B: Return a short-lived signed URL instead of the bytes. Better for MCP generally, since audio files do not belong in a tool result. This matches what was requested for Voice AI recordings in a separate idea on the Voice AI board. Option C: Expose the Twilio Recording SID on TYPE_CALL messages. The Call SID is already present as altId. Only the Recording SID is missing, and clients could then construct the URL themselves. BROADER POINT This is not really a feature request. It is a spec bug with a one line fix, and it will silently affect any other binary-returning operation in the registry that carries the same wrong content type. Worth auditing the generated registry for others. Related and now largely shipped: https://ideas.gohighlevel.com/highlevel-mcp/p/expose-call-call-transcription-and-recording-endpoints-in-the-highlevel-mcp-serv That request asked for three tools. All three now exist. Transcription works. Recording is the one that is broken.

I'm using your MCP server ( services.leadconnectorhq.com/mcp ) to connect my GHL account to Claude. Right now the available tools cover contacts, tags, opportunities, and conversations, but two things I rely on daily in the GHL dashboard aren't exposed through MCP yet: Contact notes — the Notes API (GET /contacts/{contactId}/notes) that's already part of your REST API. Call transcripts — I have AI call transcription turned on and can see full transcripts in-app. I'd like the MCP server to expose that transcript data per contact/call, the same way it's already accessible in the GHL UI. Access to both are critical for creating touch plans to contacts that are customized and can reference past conversations and notes associated with the contact. Both of these already exist in your platform — I'm asking specifically for MCP tool coverage so Claude can read them the way it already reads my contacts and conversations. Is this something on your MCP roadmap, or is there a feature-request channel where I should log it? Thanks, Marc Santos RapidFund Lending

We need the ability to create, read, update, delete, search, and list every single object in the GHL so that we can have the AI agents work optimally. Right now its very limited.

Call transcripts are visible in the HighLevel web UI, but they are not exposed by the official HighLevel MCP server. The REST API already has dedicated endpoints: •  GET /conversations/locations/:locationId/messages/:messageId/transcription •  Get Recording by Message ID •  Download transcription by Message ID The official MCP server ( https://services.leadconnectorhq.com/mcp/ ) currently includes 36 tools and covers conversations, but it does not provide any tool that wraps these transcription or recording endpoints. As a result, AI agents connected via MCP cannot retrieve call transcript text or recordings, even though the data exists in the account. I need MCP tools that: • Return the full transcript text for a given message ID • Return the recording URL/file for a given message ID • Optionally download the transcript file This is a high-impact feature for Voice AI, call automation, compliance, and knowledge-base workflows. Please add MCP tools for: •  get_message_transcription(messageId, locationId) •  get_message_recording(messageId, locationId) •  download_transcription(messageId, locationId)

would love to see GHL expand MCP beyond basic data retrieval and simple CRM actions. The real opportunity is for MCP to help users safely build, document, optimize, and manage more of the GHL ecosystem from tools like Claude, Codex, and other AI workspaces. GHL is already an all-in-one platform. Expanded MCP access could make it feel like a true AI-powered business operating system. Here are the biggest features I’d love to see: Funnel and landing page access It would be amazing if MCP could create, edit, duplicate, and publish funnels and landing pages. For example, AI could help us create new funnels, update page copy, edit buttons and links, connect forms and offers, update SEO settings, save pages as drafts, and compare versions before publishing. This would help users go from strategy to implementation much faster. Full workflow visibility and export This is one of the biggest needs. I would love for MCP to be able to see all workflows/automations and every step inside each one. Many GHL users have accounts with years of automations built up over time. It can be hard to know what’s active, outdated, duplicated, or causing problems. AI could help us find broken logic, identify duplicate automations, spot missing tags or triggers, clean up old workflows, simplify customer journeys, document what each workflow does, and optimize workflows for better results. At the very least, it would be incredibly helpful to have a CSV export that shows all workflows and the steps inside each one. Workflow creation and editing Beyond viewing workflows, it would be amazing if MCP could safely create and edit workflows. For example: create new workflows, duplicate existing workflows, edit triggers, edit conditions, edit actions, enable/disable workflows, and validate workflow logic before publishing. This would be huge for agencies, teams, and business owners managing complex automation systems. Email campaign and template management I’m also hoping GHL adds MCP functionality for email, similar to what Kit has started doing. It would be incredibly useful if AI could help create email campaigns, edit templates, schedule broadcasts, build automated sequences, pull performance stats, recommend subject line tests, organize old templates, and identify low-performing emails. For people using GHL as their email platform, this would be a major upgrade. Community management features We use GHL to manage a community, and I would love to see MCP support community features too. For example, AI could help schedule community posts, respond to comments, summarize community activity, identify unanswered posts, pull common questions, create calendar events, draft engagement prompts, and manage recurring community content. This would make the community feature much more powerful for businesses trying to create engagement at scale. Account-wide asset search It would be extremely helpful if MCP could search across the whole account. For example: Where is this old offer mentioned? Which workflows use this tag? Which emails mention this checkout link? Which funnels connect to this form? Where is this product currently being sold? This would save a massive amount of time and reduce errors when updating offers, links, branding, or customer journeys. Reporting and analytics access AI would be much more useful if it could analyze performance data inside GHL. I’d love MCP access for funnel conversion rates, email open/click rates, workflow performance, appointment show rates, product sales, attribution data, lead source performance, failed payments, and community engagement. Then users could ask AI where a funnel is leaking, which emails need improvement, or which lead sources are actually converting. Safer AI permission controls To make these features practical, we’d also need strong safety controls: * read-only mode * draft-only mode * approval before publishing * approval before sending emails * approval before deleting anything * tool-level permissions * subaccount-level permissions * audit logs of AI actions * rollback options for AI-made changes The big picture: GHL MCP should not just help AI retrieve data. It should help AI safely build, audit, optimize, document, and operate the entire GHL ecosystem. This would save business owners and teams so much time, make messy accounts easier to manage, help agencies scale implementation, and truly set GHL apart from other platforms.

We need a MCP tool for being able to manage all the tags on the system. In particular list all of them. Use case: Before adding a new tag, check all available tags to see if there is a suitable one to add, rather than create a new tag. Ultimately when it comes to tags we should be able to Create Tag Rename Tag Get List of All Tags Delete Tag via MCP as well as add/remove tags to a contact.