# Goodcall MCP MCP > Goodcall connects your AI client to a virtual receptionist fleet. It lets you manage every aspect of your business phone line—from scheduling appointments and reviewing call transcripts to analyzing total call volume and spotting missed calls needing follow-up. ## Overview - **Category:** customer-support - **Price:** Free - **Tags:** virtual-receptionist, appointment-scheduling, ai-voice-agent, call-handling, customer-inquiries, automated-phone-system ## Description Need an AI agent that handles incoming business calls so you don't? This MCP connects your preferred AI client to a full virtual receptionist system. You get control over the entire phone line, letting your agent take messages, book meetings, and answer questions—all without ever putting people on hold. It centralizes all call data into one place. Your agent handles calls, but this MCP lets you see everything: who called, what they talked about (full transcripts), how many appointments were booked, and even if they missed a number that needs calling back. If you're building complex workflows, connecting to the Vinkius catalog makes it easy to route call data and booking requests into any agent or system. ## Tools ### check_goodcall_status Verifies if the connection between your AI client and Goodcall is working correctly. ### get_agent Retrieves specific details about a single virtual phone agent's configuration. ### get_analytics Pulls comprehensive reports on call volume, answer rates, and booking conversions over time. ### get_call_summary Generates an AI-written summary of a call's purpose, outcome, and key takeaways. ### get_call Shows the basic metadata for a specific phone call, like when it happened and who called. ### get_transcript Retrieves the full, word-for-word conversation transcript between your agent and the caller. ### list_agents Provides a list of every virtual phone agent configured for your business. ### list_bookings Shows all scheduled appointments that were created by the AI agents during customer calls. ### list_calls_by_agent Filters and lists all calls, focusing only on those managed by one specific agent. ### list_calls Lists every single call handled by your virtual agent fleet over a given period. ### list_faqs Lists the current Frequently Asked Questions entries configured for any given agent, helping you check knowledge coverage. ### list_missed_calls Identifies all calls that were missed or abandoned, prioritizing those that need immediate follow-up. ### update_agent Allows you to modify an existing agent's behavior settings or greeting scripts. ## Prompt Examples **Prompt:** ``` Show all calls from today and highlight any missed calls that need follow-up. ``` **Response:** ``` Today's call summary: 18 total calls handled by your AI agents. 15 answered successfully (83.3% answer rate), 3 missed calls. Missed calls needing follow-up: 1) +1 (555) 234-5678 at 9:14 AM — rang 4 times, no pickup. 2) +1 (555) 876-5432 at 11:02 AM — caller hung up during greeting. 3) +1 (555) 345-6789 at 2:30 PM — voicemail left. 2 bookings made today. Would you like to see the call transcripts or update the agent scripts? ``` **Prompt:** ``` Show me the summary and transcript of the last call handled by the main office agent. ``` **Response:** ``` Last call for 'Main Office Agent' (agent_001): call_5678, duration 3m 42s, caller: +1 (555) 901-2345. AI Summary: Customer called about business hours and pricing for a dental cleaning. The agent confirmed operating hours (Mon-Fri 8AM-6PM, Sat 9AM-2PM) and quoted $120 for a standard cleaning. Customer booked an appointment for Thursday at 10AM. Outcome: booking completed. Transcript available — 14 exchanges between caller and agent. Would you like to read the full transcript or check the FAQ entries? ``` **Prompt:** ``` Show analytics for all my agents this month — answer rates, bookings, and total call volume. ``` **Response:** ``` Monthly analytics: Total calls: 342. Answer rate: 89.5% (306 answered, 36 missed). Bookings: 78 appointments made (25.5% booking conversion). Average call duration: 2m 48s. Peak hours: 10-11 AM (52 calls) and 2-3 PM (41 calls). Agent breakdown: 1) 'Main Office' — 198 calls, 92% answer rate, 45 bookings. 2) 'After Hours' — 89 calls, 85% answer rate, 22 bookings. 3) 'Spanish Line' — 55 calls, 87% answer rate, 11 bookings. Would you like to update agent scripts or review missed calls? ``` ## Capabilities ### Manage your AI agents You can list all active virtual phone agents and update their greeting scripts or behavior settings. ### Review detailed call records Retrieve full details for any single call, including the conversation transcript and an AI-generated summary of key topics and outcomes. ### Track missed calls and bookings See a list of all abandoned or missed calls that require follow-up, alongside viewing every appointment the agent successfully booked during a call. ### Analyze performance metrics Generate aggregate reports showing total call volume, answer rates, and booking conversion trends across your entire fleet. ## Use Cases ### Reviewing a complex sales day The ops manager wants to know how many appointments were booked today. They prompt their agent: 'Show me all calls from yesterday and list bookings.' The agent uses `list_calls` then `list_bookings` to provide a consolidated report, saving the manager hours of cross-referencing. ### Training a new virtual employee A customer service leader needs to check if the 'After Hours' agent knows about our holiday policy. They prompt: 'List FAQs for After Hours.' The agent uses `list_faqs` and, if gaps appear, the leader can use `update_agent` to fix the scripts. ### Investigating a drop in calls A small business owner notices call volume dipped last week. They prompt: 'Compare yesterday's performance against last week using get analytics.' The agent uses `get_analytics` to show the decline and suggests they check `list_missed_calls` for lost opportunities. ### Following up on a key prospect A manager needs context from the last conversation. They prompt: 'Show me the summary and transcript of the call with Mr. Smith.' The agent uses `get_call_summary` and then `get_transcript`, giving the manager all the necessary talking points for a follow-up email. ## Benefits - Stop guessing about missed leads. Use `list_missed_calls` to immediately flag numbers that rang but went unanswered, so you never lose a potential customer. - Cut down on reporting time by running `get_analytics`. You get total call volume, answer rates, and booking conversion percentages in one view, instead of manually compiling data from multiple tabs. - When you need to train an agent or update its knowledge base, use `list_faqs` to verify that the right information is configured for every line. - Don't just see a call happened; understand it. Use `get_call_summary` to get a quick, AI-written writeup of what the customer needed and what was decided. - Deep dive into conversations with `get_transcript`. This tool gives you the full record, letting you analyze exactly how your agent responded to tough questions. - Keep track of who's doing what by using `list_agents` and `update_agent`, ensuring every virtual employee has the correct scripts. ## How It Works The bottom line is that instead of logging into multiple dashboards, all your phone operations—calls, bookings, and agent stats—are available right inside your AI chat window. 1. Subscribe to this MCP in Vinkius and enter your Goodcall API Key into your AI client. 2. Your agent accesses the tools, performing actions like listing agents or retrieving call transcripts based on your prompt. 3. The data is returned to your client instantly, allowing you to review analytics, update scripts, or check booking status. ## Frequently Asked Questions **How do I check call volume using `get_analytics`?** You simply ask the agent to pull analytics for a specific time frame. The tool returns metrics like total calls and answer rates, helping you see if your staffing needs adjusting. **Can I find out why a call didn't result in a booking using `get_call_summary`?** The summary analyzes the conversation flow to pinpoint outcomes. It tells you if a booking was missed and provides context, like 'Customer asked about pricing but left before getting an answer.' **What is the best way to check agent performance? Should I use `list_agents` or `get_analytics`?** Use `get_analytics`. While `list_agents` shows who you have, `get_analytics` uses that data to track actual call metrics and booking conversion rates for each agent. **I missed a number; how do I follow up? Can `list_missed_calls` help?** Yes. Running `list_missed_calls` gives you a dedicated list of abandoned or uncollected calls, prioritizing them so you know exactly who to call back first. **If my connection fails, how do I use `check_goodcall_status` to confirm if the API key is working?** You must run `check_goodcall_status` first. This confirms your account's general connectivity and validates that your API key has permission to communicate with Goodcall's services before you attempt any detailed data pulls. **After I adjust an agent’s greeting or scripts, how do I use `update_agent` to make sure the changes take effect immediately?** You need to call `update_agent` and pass the full new configuration payload. This action forces Goodcall to push those updated behavior settings directly to the active virtual phone line. **How can I use `list_calls_by_agent` to generate a comprehensive history for one specific AI representative?** `list_calls_by_agent` filters all records by that agent's unique ID. This function gives you an easily reviewable timeline of every call and interaction handled by that single virtual resource. **If I need the raw, minute-by-minute conversation text, what tool retrieves the full dialogue using `get_transcript`?** `get_transcript` pulls every exchange between the caller and agent. It provides the complete, unsummarized dialogue necessary for deep analysis or compliance review. **Can I review what my AI phone agent said during a customer call?** Yes. Use `get_transcript` with a Call ID to retrieve the full conversation transcript between the AI agent and the caller. For a quick overview, use `get_call_summary` which provides an AI-generated summary with key topics discussed and the call outcome (e.g., booking made, question answered, callback requested). **Can I track missed calls and see which ones need follow-up?** Yes. The `list_missed_calls` tool retrieves all calls that were missed or abandoned, including caller phone number, timestamp, and any partial interaction data. This helps you prioritize follow-up callbacks and identify peak call times when your agents may be overloaded. **Can I see appointments booked by the AI agent during calls?** Yes. The `list_bookings` tool retrieves all appointments booked by the AI agent during customer calls, including date, time, caller details, and the associated call ID. Use `get_analytics` to track your booking conversion rate — the percentage of calls that result in a scheduled appointment.