Chatforma
Chatforma is a chatbot automation platform for managing bots, users, segments, broadcasts, dialogs, forms, notifications, and variables.
Verdict
Common use cases
- Triage support tickets from bot conversations
- Pull lead context into sales planning docs
- Audit bot variable usage across user segments
- Draft personalized follow-ups for open dialogs
- Summarize weekly conversation volume by segment
Integration
- Vendor
- Chatforma
- Category
- communication
- Auth
- API_KEY
- Tools
- 10
- Composio slug
chatforma
Tools
- Get User Variable
Get the current value of one bot variable for one bot user.
- List Bots
List bots belonging to the connected Chatforma account so their IDs can be used in bot-scoped tools.
- List Dialog Messages
Return one page of messages exchanged in a specific user's bot dialog, with a cursor for continuing the history.
- List Predefined Messages
List predefined messages configured in a bot so a message ID can be selected for sending.
- List Segments
List the user segments configured for a bot, including segment IDs needed for targeted sends.
- List Users
List a bot's users, members of one segment, or users with open dialogs; choose the view that matches the task.
- List Variables
List variables configured for a bot, including IDs and types needed to read user-specific values.
- Send Dialog Message
Immediately send a user-visible text message into a specific user's bot dialog. This irreversible action may contact a real user.
- Send Predefined Message
Send a configured bot message to one user or dispatch it to a segment. This irreversible action may contact one or many real users.
- Send Text Dispatch
Create a user-visible text dispatch for one bot user or a segment. Delivery may be immediate or scheduled where supported and cannot be undone through this API.
Setup
Setup guide
- 11. Open your Switchy workspace settings and navigate to the Integrations tab. 2. Click 'Add Integration' and select Chatforma from the communication category. 3. In a separate browser tab, log into your Chatforma account and navigate to Settings > API Keys. 4. Generate a new API key with read and write permissions for bots, users, and messages. 5. Copy the key and paste it into the Switchy connection dialog, then click 'Connect'. 6. Switchy will verify the key and display a list of your bots to confirm the connection succeeded. 7. Inside any Project, type '@Chatforma list bots' and send the message to confirm the MCP responds with your bot roster. 8. To send a test message, first run '@Chatforma list users' for a bot ID, pick a user, then '@Chatforma send dialog message' with that user's ID and a short greeting.
What teammates see: by default, memories from Chatforma are scoped to the Project (PROJECT visibility) - you can mark any memory PRIVATE or share it ORG-wide.
Works well with
Top models
Compatibility data appears once enough Projects have used this MCP together with a given model.
How Switchy teams use it
Starter prompts
Summarize Open Conversations
@Chatforma list users with open dialogs for bot ID [your_bot_id], then retrieve the last five messages from each dialog and summarize the main topics customers are asking about.
Audit Variable Coverage
@Chatforma list variables for bot ID [your_bot_id], then for each variable check how many users in segment [segment_id] have a value set and report any variables with low coverage.
Draft Targeted Follow-Up
@Chatforma list users in segment [segment_id] for bot ID [your_bot_id], retrieve the most recent dialog message from each, and draft a follow-up message that references their last question.
Compare Predefined Messages
@Chatforma list predefined messages for bot ID [your_bot_id] and recommend which message would work best for re-engaging users who haven't replied in seven days.
Export Conversation Sample
@Chatforma list dialog messages for user ID [user_id] in bot ID [your_bot_id], retrieve the complete conversation, and format it as a support ticket with timestamps and user variables.
Example outputs
Illustrative - representative of the model's voice and quality, not literal recordings.
@chatforma list all users in the 'Trial Expired' segment for our onboarding bot and show me their signup dates
Found 47 users in the 'Trial Expired' segment (ID: seg_8x2k). Here's a sample: User alice@example.com signed up 2024-01-15, last active 2024-02-10. User bob@startup.io signed up 2024-01-18, last active 2024-02-08. User carol@tech.co signed up 2024-01-22, last active 2024-02-12. The segment includes users who haven't upgraded within 30 days of their trial start. All 47 users have the 'trial_end_date' variable set between January 10–25, 2024.
This example combines List Segments and List Users to filter by audience. Requires read scope for the bot's user data. Chatforma returns paginated results; large segments may need multiple calls. Signup dates come from user variables, so the bot must track that field.
@chatforma send a message to user ID usr_4h9p in the support bot saying 'Your refund has been processed and will appear in 3-5 business days'
Message sent successfully to user usr_4h9p in bot 'Customer Support' (bot_3k7m). The message 'Your refund has been processed and will appear in 3-5 business days' now appears in their dialog history. Delivery timestamp: 2024-03-14 16:42:18 UTC. This message is visible to the user immediately and cannot be unsent.
Send Dialog Message is irreversible and contacts a real person. Use cautiously—confirm the user ID and message content before executing. Requires write scope. If the user has notifications enabled, they'll receive a push/email alert. No undo mechanism exists in the Chatforma API.
@chatforma pull the last 20 messages from user usr_2n5t's dialog in the sales bot and summarize what issue they're reporting
Retrieved 20 messages from usr_2n5t's dialog in bot 'Sales Inquiry' (bot_9w1x). The user initially asked about enterprise pricing on March 10, then followed up March 12 asking if annual contracts include priority support. On March 13, they mentioned their team size (50 users) and requested a custom quote. Most recent message (March 14, 10:15 AM): 'Can someone call me today?' Summary: User is a qualified enterprise lead seeking pricing for 50 seats with priority support, now requesting a phone conversation.
List Dialog Messages returns paginated history; 20 messages may span multiple API calls depending on page size. This example pairs retrieval with AI synthesis to extract intent. Requires read scope. Message timestamps and sender (user vs. bot) help the AI reconstruct the conversation flow.
Use-case deep-dives
When your support bot needs a human escape hatch
A 6-person SaaS support team runs a Chatforma bot that handles password resets and billing questions. When a user hits the bot's limits, the team uses this MCP to pull the dialog history, check user variables (like account tier or last purchase date), and send a handoff message directly into the conversation. The MCP's List Dialog Messages and Send Dialog Message tools let an AI agent read context and respond without switching tabs. This works until you're handling more than 30 handoffs a day—at that scale, you need a proper ticketing system with SLA tracking, not ad-hoc message sends. If your bot conversations stay under 50 messages per user and your team is small enough to work from a shared Slack channel, this MCP turns Chatforma into a lightweight support triage layer.
Segment-based outreach without leaving your AI workspace
A 3-person growth team at a B2C app wants to send a re-engagement message to users who haven't opened the bot in 14 days. They use this MCP to list segments, filter for the dormant cohort, and queue personalized messages using variables like first name and last active date. The List Segments and List Users tools surface the targeting data; Send Dialog Message delivers the outreach. This approach wins when you're running 2-3 campaigns a month and your segment logic is simple (single-condition filters). If you're A/B testing message variants or sending daily drip sequences, Chatforma's native campaign builder is faster—the MCP adds latency because each send is a separate API call. For low-frequency, high-context sends where an AI agent can draft the message based on user history, this MCP keeps the workflow in one place.
Proactive outreach triggered by user behavior signals
A 4-person customer success team monitors a Chatforma bot used by 200 enterprise trial users. When a user's variable for 'feature_adoption_score' drops below a threshold, the team wants an AI agent to send a check-in message offering a walkthrough call. The MCP's Get User Variable tool reads the score; List Predefined Messages pulls the template; Send Dialog Message delivers it. This works because the team already tracks meaningful variables in Chatforma and the send volume is manageable (maybe 5-10 check-ins a week). If your variables are messy or you're sending hundreds of messages daily, the per-call latency stacks up and you'll want a webhook-driven system instead. For teams that treat their chatbot as a CRM-lite and want AI-assisted outreach without building custom integrations, this MCP bridges the gap.
Frequently asked
What does the Chatforma MCP let me do in Switchy?
It connects your Chatforma chatbots to Switchy so AI agents can read conversation history, check user variables, and send messages into live dialogs. You can automate responses based on segment membership, pull predefined messages, and inspect which users have open conversations—all without leaving your Switchy workspace.
Do I need admin access to connect Chatforma?
You need a Chatforma API key with write permissions if you want agents to send messages. Read-only keys work for listing bots, users, and variables, but Send Dialog Message will fail. Generate the key in your Chatforma account settings and paste it into Switchy's integration page.
Can the MCP send broadcast messages to all bot users?
No. Send Dialog Message targets one user's dialog at a time. If you need to broadcast, your agent must loop through List Users or List Segments and call Send Dialog Message once per recipient. That's intentional—Chatforma treats broadcasts as a separate feature outside the MCP scope.
Why use this instead of Chatforma's dashboard or API directly?
The MCP wraps Chatforma's API so your AI agents can query conversation context and respond in real time without you writing integration code. If you already have custom scripts calling Chatforma's REST endpoints, keep them. Use the MCP when you want agents to handle support triage or variable lookups as part of a larger workflow.
Who on my team should connect the Chatforma integration?
Whoever owns your Chatforma account and can generate API keys. Once connected, any Switchy team member can invoke the tools in their agents—but remember that Send Dialog Message posts to real users, so restrict access to people who understand your bot's tone and compliance rules.