Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Description from the maker (original English)
ElevenLabs Conversational AI: agents, calls, conversations, and knowledge base for MCP hosts
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We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
ELEVENLABS_API_KEY, MCP_WORKSPACE_PATHValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"elevenlabs-agents": {
"command": "npx",
"args": [
"-y",
"@mindstone/mcp-server-elevenlabs-agents"
],
"env": {
"ELEVENLABS_API_KEY": "your-value",
"MCP_WORKSPACE_PATH": "your-value"
}
}
}
}Run this in your terminal
claude mcp add elevenlabs-agents --env ELEVENLABS_API_KEY=your-value --env MCP_WORKSPACE_PATH=your-value -- npx -y @mindstone/mcp-server-elevenlabs-agentsFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"elevenlabs-agents": {
"command": "npx",
"args": [
"-y",
"@mindstone/mcp-server-elevenlabs-agents"
],
"env": {
"ELEVENLABS_API_KEY": "your-value",
"MCP_WORKSPACE_PATH": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"elevenlabs-agents": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@mindstone/mcp-server-elevenlabs-agents"
],
"env": {
"ELEVENLABS_API_KEY": "your-value",
"MCP_WORKSPACE_PATH": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
MCP_WORKSPACE_PATH envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026
The registry name was verified with the GitHub account mindstone, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
You need to fill in: ELEVENLABS_API_KEY
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.2.1) reached the registry 3 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server
Servers in the same category from other makers, sorted by stars.
Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Let any LLM watch a video locally — and search everything it has ever watched.
Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
ElevenLabs Conversational AI MCP server for Model Context Protocol hosts. Inspect and author voice agents, review conversation transcripts and recordings, manage phone-number assignments, place outbound calls, submit or monitor scheduled batch calls, and write to the knowledge base through the ElevenLabs ConvAI API.
ELEVENLABS_API_KEY)STATUS.jsonAfter clicking the button, your host will prompt you to fill: ELEVENLABS_API_KEY.
Manual config for Claude Desktop / Claude Code / Goose / Continue.dev (ElevenLabs Agents)
{
"mcpServers": { "ElevenLabs Agents": { "command": "npx", "args": [ "-y", "@mindstone/mcp-server-elevenlabs-agents" ], "env": { "ELEVENLABS_API_KEY": "" } } } }
cd <path-to-repo>/connectors/elevenlabs-agents
npm install npm run build
node dist/index.js
ELEVENLABS_API_KEY — ElevenLabs API key (starts with sk_)MCP_WORKSPACE_PATH — optional sandbox root for knowledge-base file uploadsMCP_HOST_BRIDGE_STATE — optional path to a host bridge state file used for credential managementMINDSTONE_REBEL_BRIDGE_STATE — backwards-compatible alias for MCP_HOST_BRIDGE_STATE{
"mcpServers": { "ElevenLabs Agents": { "command": "node", "args": [" /connectors/elevenlabs-agents/dist/index.js"], "env": { "ELEVENLABS_API_KEY": "your-api-key" } } } }
configure_elevenlabs_agents_api_key — Save your ElevenLabs API keylist_agents — List voice agents in the workspaceget_agent — Get one agent, including prompts and nested conversation configcreate_agent — Create a new agent from a user-friendly authoring surfaceupdate_agent — Partially update one agent via PATCH deep-merge semanticsduplicate_agent — Duplicate an existing agent before experimentingdelete_agent — Permanently remove an agentsimulate_conversation — Test an agent with a simulated user message before telephony worklist_agent_tools — List webhook/client/system tools available to agentsadd_agent_tool — Add a webhook or client tool to the workspacelist_conversations — List conversations, optionally filtered by agent/date/successget_conversation — Get a full conversation transcript and analysisget_conversation_audio — Download the conversation recording to a tmp filesubmit_conversation_feedback — Submit like/dislike feedback on a reviewed conversationlist_phone_numbers — List configured phone numbersget_phone_number — Get one phone number and its label/assignmentimport_phone_number — Import a Twilio or SIP trunk number into the workspaceupdate_phone_number — Update one phone number label and/or assigned agentdelete_phone_number — Permanently remove an imported phone numbermake_outbound_call — Place one outbound call after resolving the phone-number provider automaticallysubmit_batch_call — Submit a multi-recipient batch, optionally scheduled for the futurelist_batch_calls — List recent batch-call jobs in the workspaceget_batch_call — Inspect one batch job, including per-recipient statusescancel_batch_call — Cancel a queued or scheduled batch jobretry_batch_call — Retry a previously submitted batch joblist_knowledge_base_docs — List knowledge-base documentsget_knowledge_base_doc — Get one knowledge-base document (metadata + /content body, capped ~50KB)add_knowledge_base_document — Add a KB document in text, file, or URL modedelete_knowledge_base_document — Delete a KB document, optionally with forceget_knowledge_base_rag_index_status — Check whether a document is indexed and retrievablerebuild_knowledge_base_rag_index — Trigger (re)indexing of a KB documentAll external text returned by the ElevenLabs API is wrapped in envelopes before it reaches the model. This is especially important for conversation transcripts, which can contain attacker-controlled caller speech. Enveloping is deny-by-default: anything that is not a recognised structural value (IDs, enums, timestamps, phone numbers) is wrapped, including responses whose root is a bare JSON value rather than an object.
The same walk runs on every response surface — agents, conversations, knowledge base, phone numbers, simulations, and outbound/batch calls. No surface carries a list of known prose field names, so a text field added upstream (an agent name, a workflow branch name, a future summary) is enveloped from the day it first appears in a response.
Nor does an unexpected *shape* route text around the walk. A response whose root is a bare JSON value, a list whose items are bare strings, and a transcript field carrying a string or an object where an array of turns was expected all go through the same deny-by-default walk rather than being returned unchanged.
Because reads come back enveloped, the agent authoring tools strip one envelope from the values they are given. Copying a language, model id, prompt, or advanced_config fragment out of get_agent and back into update_agent therefore stores the original text upstream rather than the envelope around it.
The structural literal exemptions in the walk are path-aware and value-shape-aware, not key-name-based. Inside arbitrary collaborator-authored maps — webhook request_headers, advanced_config passthroughs, JSON-Schema parameter fragments, and the caller-authored open maps submitted with call initiation (conversation_initiation_client_data, conversation_config_override, custom_llm_extra_body, overrides, which ElevenLabs reflects on the conversation, call, and batch-call surfaces) — key names are data rather than schema, so no string stays literal there at all: a property named status in a request-header map is collaborator text, not a trusted enum, and is enveloped whatever its value looks like. Because advanced_config is deep-merged into the config body before it is sent upstream, its reflected shape carries no advanced_config ancestor to key off; on the agent and workspace-tool surfaces a string therefore also stays literal only when every ancestor key from the surface root is a known schema position, so a flattened passthrough fragment (for example tool_config.custom.status) is enveloped however structural its key names and value shape look. Elsewhere on trusted paths, a string only stays literal under id/status/role/type keys when it is id/enum-shaped (no whitespace, no : or /, and not phrase-shaped or built from instruction-shaping words — alphabet shape alone cannot tell an identifier from whitespace-free authored text such as IGNORE_PRIOR_INSTRUCTIONS), under timestamp only when it is ISO-8601-shaped, and under phone-number keys only when it is E.164. Values under credential-shaped keys (token, sid, *_secret, *_password, *_api_key) are replaced with [redacted] instead of being passed on at all, and import_phone_number additionally strips the exact submitted credentials — the Twilio SID/token pair, and SIP trunk credential values such as a trunk username — from any success payload or upstream error detail that reflects them.
URLs the connector asks ElevenLabs to dereference server-side must be public https:// addresses. This covers webhook tools via add_agent_tool, URL-mode knowledge-base documents, and every url-keyed string in the agent authoring tools' advanced_config (create_agent / update_agent) — ElevenLabs fetches custom_llm.url on every conversation turn and dereferences platform_settings webhook URLs, so the merged agent body is validated recursively before any upstream call. Non-HTTP schemes, plain HTTP, embedded credentials, loopback/private/link-local/CGNAT/multicast IP literals (including the cloud-metadata address 169.254.169.254), IPv4-mapped/NAT64/6to4/Teredo and documentation IPv6 ranges, localhost-style hostnames, and single-label hostnames are rejected before any upstream call; trailing root-label dots are stripped before classification, so DNS-equivalent spellings such as localhost. are rejected too. A public hostname can still resolve or redirect to an internal address once ElevenLabs fetches it — that residual DNS/redirect trust boundary is inherent to server-side dereferencing and is not closed by this validation. add_agent_tool's advanced_config deep-merges last but cannot set first-class fields (type, name, description, expects_response, api_schema.url, api_schema.method), and the merged tool config is revalidated before it is sent.
Outbound numbers are validated in E.164 format before any billing-surface call is sent upstream. Scheduled batches run on ElevenLabs' servers even if the client app is closed, so they should be monitored with list_batch_calls / get_batch_call and stopped with cancel_batch_call when needed.
FSL-1.1-MIT — Functional Source License, Version 1.1, with MIT future licence. The software converts to MIT licence on 2030-04-08.
files/readModes version 1 is an experimental extension used by these connectors, not part of the MCP standard. A compatible host (the app running the connector) decides which input files a tool call may read. The connector opens only the host-approved physical path, after resolving symlinks. The host supplies this permission information with each call; it is not a tool argument you need to set. Missing or invalid permission information, or a file absent from the approved list, stops the read.
Clients that do not negotiate this extension keep the connector's existing standalone file restrictions. This extension changes input-read permis
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