# Voiceflow MCP > Voiceflow MCP connects your conversational AI build directly into any agent client. This lets you design, test, and debug complex dialogue flows using a visual builder, without writing code or deploying new endpoints. You can simulate user interactions, query the knowledge base for answers, and inspect every conversation transcript right from your chat interface. ## Overview - **Category:** industry-titans - **Price:** Free - **Tags:** conversational-ai, chatbot-design, rag-pipeline, dialog-flow, prototyping, ai-agent-testing ## Description This connector gives your AI agents an escape hatch. Instead of building massive backend services just to test if a chatbot works, you connect it directly through this MCP. You can send messages to simulate user conversations and immediately see how the agent responds across all its logic paths. Need to check what data the conversation is currently holding? It lets you retrieve, update, or even reset the user's entire session state for debugging. If your agent uses a private knowledge base, you don't have to guess; you can query the documents and list exactly which files are powering the answers. Monitoring isn't just about seeing success messages. You get full visibility into what every AI agent is doing through Vinkius AI Analytics—you see the data flow and tool calls in real time. This means when you build complex, multi-step workflows that chain together different services, you know exactly where the conversation broke down. ## Tools ### delete_state Resets the entire user conversation session variables. ### get_feedback Fetches the current upvote/downvote status for a project or interaction. ### get_project Retrieves detailed information about a specific Voiceflow project. ### get_state Reads and returns the user's current conversation variables and state data. ### get_transcript Gets the full details for one specific saved conversation transcript. ### interact Sends a message to your agent, triggering the conversational flow logic. ### list_kb_docs Lists all the documents currently loaded into the knowledge base. ### list_kb_tags Shows available tags used for organizing and filtering KB documents. ### list_projects Retrieves a list of all existing Voiceflow projects under your account. ### list_transcripts Lists the IDs and details of stored user conversation transcripts. ### query_kb Asks the knowledge base directly to find an answer based on provided context or query. ### save_state Updates specific variables within the user's current conversation state. ## Prompt Examples **Prompt:** ``` List all my Voiceflow projects. ``` **Response:** ``` I've retrieved your projects. You have access to: 'Customer Support Bot', 'Sales Assistant v2', and 'Internal FAQ Bot'. Which one would you like to inspect? ``` **Prompt:** ``` Ask my KB: 'What is the return policy for international orders?' ``` **Response:** ``` According to your Knowledge Base, international orders can be returned within 30 days, but the customer is responsible for shipping costs. Would you like the source document details? ``` **Prompt:** ``` Show me the last 3 transcripts for the 'Customer Support Bot'. ``` **Response:** ``` I've fetched the transcripts. Here are the 3 most recent sessions: User_8823 (Success), User_8824 (Dropped), and User_8825 (Handoff to Human). Shall I retrieve the dialogue for the dropped session? ``` ## Capabilities ### Test Agent Responses Send messages to your agent to instantly test conversational flows and expected reactions. ### Query Knowledge Base Ask the agent's connected knowledge base a question and get answers, or list the documents that power those answers. ### Manage Session State Get, update, or completely reset the user's conversation variables to fix complex logic bugs. ### Review Conversation History List and fetch full transcripts for any project so you can audit how users actually talk to the bot. ### Monitor Project Health Retrieve user feedback (upvotes/downvotes) and monitor project configurations live. ## Use Cases ### The QA team needs to test a new refund path. Instead of manually entering data into a staging environment, the agent client calls `interact` to start the conversation. The developer then uses `get_state` to check if the system correctly recorded the user's ID and purchase date throughout the dialogue. ### A Product Manager wants to know why users drop off. The PM asks the agent client to list all conversation transcripts. They review the results, identify a pattern of failure, and then use `get_feedback` to confirm if that pain point matches low user ratings. ### A Developer is debugging complex logic. The developer notices the agent is using an old variable. They call `delete_state` to wipe the current session, then use `save_state` immediately to inject the correct variables and test the fixed flow. ### A Content team needs to verify policy answers. The agent client asks the system about a new tax rule. The developer uses `list_kb_docs` first, confirming the source material is present, then relies on `query_kb` to ensure the answer reflects only the official document. ## Benefits - Debug agent logic instantly: Use `get_state` and `save_state` to read or write user variables, allowing you to fix state bugs without manual backend changes. This is critical when building complex multi-step processes. - Audit conversations thoroughly: Instead of relying on limited logs, you can list and fetch full conversation transcripts using `list_transcripts` and `get_transcript`, giving you a complete picture of user behavior for quality assurance. - Master your knowledge base: You don't just ask questions. Use `list_kb_docs` to see what data is available and then use `query_kb` to get answers, ensuring the agent pulls from the right source material every time. - Keep track of project status: Get an immediate view of overall performance by calling `get_feedback`, letting you know if users are struggling or loving a specific flow. This helps prioritize development efforts. - Inspect everything: The ability to list projects via `list_projects` lets you manage your entire conversational portfolio from one place, simplifying the operational oversight of multiple bots. ## How It Works The bottom line is you manage your entire conversational ecosystem from one single AI client connection. 1. Subscribe to this MCP and provide your Voiceflow API Key and Version ID. 2. Your agent client connects, making the connector available for use in natural conversation prompts. 3. You ask your agent to perform an action, like listing all projects or querying a specific document, and it executes the task. ## Frequently Asked Questions **How do I use the Voiceflow MCP to debug my agent?** Use `get_state` to read what variables the user currently has in session. If they are wrong, call `delete_state` and then use `save_state` to inject the correct values for retesting. **Can I list all available projects with Voiceflow?** Yes, you can run `list_projects`. This shows you a roster of every bot or workflow you've created within your account in one simple command. **What is the difference between `query_kb` and `list_kb_docs`?** `list_kb_docs` only gives you an inventory—it shows what documents are available. You use `query_kb` when you actually need to ask a question and get an answer based on those docs. **How do I check user satisfaction using Voiceflow?** You call the `get_feedback` tool, which pulls current upvote or downvote data for your project. This lets you track sentiment without leaving your development environment. **How do I manage or reset user conversation context using `save_state`?** You use `save_state` to update or retrieve variables, allowing your agent to maintain memory across multiple turns. If the flow gets confused, calling `delete_state` resets all session data back to zero. **What metadata can I get about a specific Voiceflow project using `get_project`?** This tool pulls deep details on a selected project. You retrieve critical information like the project's version ID, its last modified date, and overall configuration status. **After calling `list_transcripts`, how do I fetch the full dialogue content for a specific session using `get_transcript`?** First, use `list_transcripts` to get the session ID. Then, pass that ID into `get_transcript` to pull every single user input and agent response from the recorded conversation. **How do I check what tags are available for my knowledge base using `list_kb_tags`?** This tool pulls a clean list of all custom tags applied across your KB documents. Checking these tags helps you organize and filter which specific sources your agent can reference during a query. **Can I query my Voiceflow Knowledge Base directly via AI?** Yes! Use the `query_kb` tool with your question. Your agent will trigger the Voiceflow RAG system and return the answer based on your uploaded documents. **How do I see the transcripts for a specific project?** Run the `list_transcripts` query with your Project ID. The agent will return a list of past conversation logs, which you can then inspect using `get_transcript`. **Is it possible to reset a user's session via AI?** Absolutely. Use the `delete_state` tool and provide the User ID. This will permanently clear the conversation history and variables for that specific session.