Typebot▌
by osdeibi
Integrate Typebot with leading AI chatbot platforms to seamlessly manage workflows and bot instances via workspace token
Integrates with Typebot's chatbot platform using workspace tokens for authentication to enable management of chatbot workflows and bot instances.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Chatbot developers managing Typebot workflows
- / Teams automating bot deployment and testing
- / Customer service teams monitoring bot performance
capabilities
- / Create and delete Typebot chatbots
- / List and update existing bots
- / Publish/unpublish chatbot workflows
- / Start chat sessions with bots
- / Retrieve conversation results and analytics
what it does
Integrates with Typebot's chatbot platform to manage chatbot workflows through natural language commands in Claude Desktop.
about
Typebot is a community-built MCP server published by osdeibi that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate Typebot with leading AI chatbot platforms to seamlessly manage workflows and bot instances via workspace token It is categorized under productivity, developer tools.
how to install
You can install Typebot in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Typebot is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
MCP-Typebot
A small MCP server that exposes Typebot’s REST API as callable tools in Claude Desktop (via STDIO). You can create, list, get, update, delete, publish/unpublish Typebots, list results, and start chats—using natural-language commands.
Features
-
createBot
Create a new Typebot in your workspace.
Required:name
Optional:workspaceId,description -
listBots
List all Typebots in your workspace.
Optional:workspaceId -
getBot
Fetch a Typebot by its ID.
Required:botId -
updateBot
Patch an existing Typebot (e.g. rename).
Required:botId,typebot(object with fields to change)
Optional:overwrite -
deleteBot
Delete a Typebot by its ID.
Required:botId -
publishBot / unpublishBot
Toggle a Typebot’s published state.
Required:botId -
listResults
Retrieve conversation results for a Typebot.
Required:botId
Optional:limit,cursor,timeFilter,timeZone -
startChat
Begin a new chat session with a Typebot.
Required:botId
Optional:chat.context
Prerequisites
- Node.js 18+
- A valid Typebot API token and workspace ID
- Claude Desktop connected to your local MCP server
Installation
git clone <repo-url>
cd mcp-typebot
npm install
npm run build
You can also install the published package directly via npm:
npm install mcp-typebot
npm start
Running
npm start
This starts the MCP server on STDIO. Claude Desktop (or any MCP client) will connect to it automatically.
Usage in Claude Desktop
Simply write natural commands like:
User: “Create me a new typebot”
Claude: “Sure—what name?”
User: “MyDemoBot”
Claude (internally invokes):@createBot {"name":"MyDemoBot"}
Or, explicitly:
@updateBot {"botId":"<your_bot_id>","typebot":{"name":"NewName"},"overwrite":true}
You can also start a chat:
@startChat {"botId":"<your_bot_id>"}
Extending
- Add new tools by implementing them in
src/tools/bots.tsand registering them insrc/index.ts. - Define a Zod schema for each tool to get automatic prompting and validation.
License
Configuring Claude Desktop
To connect Claude Desktop to this MCP server, add the following to your Claude configuration (e.g. claude_desktop_config.json):
{
"mcpServers": {
"mcp-typebot": {
"command": "node",
"args": [
"path/to/project/dist/index.js"
],
"env": {
"TYPEBOT_TOKEN": "YOUR_TOKEN_HERE",
"TYPEBOT_WORKSPACE_ID": "YOUR_WORKSPACE_ID"
}
}
}
}
Make sure the command and args point to your local built index.js, and that your .env values match those in env.
FAQ
- What is the Typebot MCP server?
- Typebot is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Typebot?
- This profile displays 75 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.5★★★★★75 reviews- ★★★★★Xiao Abebe· Dec 20, 2024
According to our notes, Typebot benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Alexander Martinez· Dec 12, 2024
I recommend Typebot for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Hassan Thompson· Dec 8, 2024
Typebot reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Xiao Chen· Nov 27, 2024
Typebot is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Hassan Khan· Nov 27, 2024
Useful MCP listing: Typebot is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Xiao Taylor· Nov 11, 2024
Typebot has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Advait Patel· Nov 11, 2024
Typebot is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Amelia Ghosh· Nov 3, 2024
Strong directory entry: Typebot surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Meera Ramirez· Oct 26, 2024
We evaluated Typebot against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Hassan Dixit· Oct 22, 2024
Typebot is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
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