Jiminny MCP. Coach sales reps with call intelligence.
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Jiminny analyzes call recordings to coach sales reps. Connect this MCP to track performance metrics, identify specific winning behaviors, and pull out concrete action items from any recorded meeting or demo.
What your AI agents can do
Check jiminny status
Verifies if the Jiminny API connection is working correctly.
Get action items
Extracts specific next steps and action items from a given call recording.
Get activity
Retrieves general details about a recorded call or meeting.
Retrieves a comprehensive list of every meeting and call in your system.
Access detailed metrics showing how individual team members are improving or falling short.
Analyzes a call's transcript and automatically generates a list of required action items.
Pulls the complete, word-for-word text record from any given call or meeting.
Provides basic identity information for team members or lists all available teams in your account.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
Jiminny with 10 Tools
Use these tools to programmatically manage recordings, pull specific stats, and get actionable insights from all your call data.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Jiminny on Vinkius019dd10echeck jiminny status
Verifies if the Jiminny API connection is working correctly.
019dd10eget action items
Extracts specific next steps and action items from a given call recording.
019dd10eget activity
Retrieves general details about a recorded call or meeting.
019dd10eget call stats
Gets overall, aggregate analytics for calls across the team.
019dd10eget coaching stats
Provides detailed coaching metrics and performance scores for a specific user.
019dd10eget transcript
Fetches the complete, word-by-word written transcript of a call recording.
019dd10eget user
Retrieves identifying and contact details for any team member.
019dd10elist activities
Lists all recorded calls and meetings that occurred in the system.
019dd10elist teams
Gets a list of all defined sales teams within your account.
019dd10elist users
Lists every individual member who belongs to the system.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Jiminny, then connect any of our 5,000+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,000+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Jiminny. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Manually auditing sales calls is pure administrative hell.
Right now, checking on a rep means logging into the recording platform, finding the call in the list, playing through 45 minutes of audio to find key moments, then manually writing up bullet points for follow-up tasks. You're jumping between tabs, copying timestamps, and praying you don't miss anything important.
With this MCP, your AI client handles it all. Instead of manual review, you ask the agent to use `get_action_items` on a call ID. The result isn't audio; it's a clean list of tasks ready for your CRM.
The Jiminny MCP gives you instant access to coaching data.
You don't have to rely on end-of-month spreadsheets or guesswork. You can ask the agent to pull specific metrics like talk-to-listen ratios using `get_call_stats` and compare them against a user’s history by calling `get_coaching_stats`. The data is immediate.
It changes everything because you move from retrospective guessing to real-time, measurable coaching. You know exactly where the team needs work.
What you can do with this MCP connector
Connecting Jiminny lets your AI client take over the manual work of sales coaching. You can programmatically list and manage every single recording in your database, pulling detailed information about who talked to whom. Need a performance audit? Your agent can query key moments across multiple meetings to build a perfect record of your sales process.
Instead of wading through hours of audio, you get specific metrics: talk-to-listen ratios or how often reps use filler words. This MCP lets your AI act as a dedicated coach and conversation architect for your whole team, making sure every call contributes directly to growth. If you're building complex reporting systems, linking Jiminny data via Vinkius is simple; your agent handles the heavy lifting.
019dd10e-ab6d-70cc-8b38-5058401a7837 
How Jiminny MCP Works
- 1 Subscribe to this MCP and grab your API Key from the Jiminny dashboard.
- 2 Connect that key to your preferred AI client (like Claude or Cursor).
- 3 Ask your agent a question, like 'What are Sarah Chen's coaching stats?' The tool does the rest.
The bottom line is you tell your AI what data you need—whether it’s call summaries or user lists—and the MCP fetches and formats it for you.
Who Is Jiminny MCP For?
Sales Managers who are tired of manually reviewing dozens of recordings; Enablement Leads needing to track coaching compliance without leaving their dashboard; Developers building custom reporting tools that need clean, structured call data.
Uses the MCP to instantly pull summaries and monitor team improvement trends across multiple reps.
Verifies individual meeting metadata and tracks coaching activity reports directly from their workflow without leaving their system.
Integrates high-speed call data into custom BI tools, pulling transcripts and stats via simple AI queries.
What Changes When You Connect
- Stop manually reviewing recordings. Use
get_transcriptto instantly pull the full text of any call, letting your agent analyze it for you. - Track performance trends across the whole team using
get_coaching_stats. You'll see if reps are improving their discovery questions week over week. - Never lose a follow-up task again. Just ask the MCP to use
get_action_itemson a call, and it lists every deliverable needed. - Audit your process by running
list_activities. You can then drill down into specific calls usingget_activityto see exactly what happened. - Maintain clean data for coaching records. Use the MCP tools to get metrics like talk-to-listen ratios and filler word counts.
Real-World Use Cases
Diagnosing a struggling rep's calls
A sales manager asks the agent: 'Show coaching stats for John Doe.' The MCP uses get_coaching_stats to provide an average score and improvement trend. This immediately tells the manager where to focus their training efforts.
Creating a post-call summary
A rep finishes a demo call and asks the agent: 'What did we decide?' The MCP uses get_action_items on the transcript. It pulls out all agreed tasks—send proposal, schedule follow up—so they can be immediately added to a CRM.
Auditing an entire month's worth of meetings
An enablement lead needs a full picture. They ask the agent to use list_activities and then iterate, pulling transcripts using get_transcript for the top 10 calls. This builds a comprehensive performance report quickly.
Integrating call data into a BI dashboard
A developer needs raw data points. They use the MCP to list all users (list_users) and then loop through get_call_stats for each user, feeding the structured metrics directly into a custom reporting tool.
The Tradeoffs
Searching by vague keywords
Just asking the agent: 'Tell me about last week's calls.' This forces the AI to guess which data set to pull, leading to incomplete or irrelevant results.
→
Be specific. Always start with listing what you need first, for example, use list_activities to narrow down the date range, then pass those IDs when calling get_call_stats.
Copy-pasting raw transcripts
Downloading a massive transcript and having to read it line by line just to find action items or names.
→
Don't read the text. Use get_action_items directly on the call ID. The MCP does the extraction for you, giving you only what matters.
Forgetting who was involved
Getting a list of calls but not knowing which rep spoke to whom or if they were in the correct team.
→
Always call list_teams and get_user first. This ensures you have the proper context (the user IDs) before calling any performance tool like get_coaching_stats.
When It Fits, When It Doesn't
Use this MCP if your primary pain point is converting raw audio or text into structured, actionable data points—like specific tasks, coaching scores, or call summaries. If you're only trying to list users and teams, a basic directory tool works fine. But when the goal is performance analysis (e.g., 'How did this rep do on discovery questions?'), Jiminny is necessary. Don't use this if your data lives in an entirely separate system (like Slack messages); you need a dedicated integration for that. If you only need to view records, just read the call logs; but if you need to analyze them and find patterns, start here.
Common Questions About Jiminny MCP
How do I list all my recorded calls using the Jiminny MCP? +
You use list_activities to get a comprehensive list of every call and meeting. This tool returns IDs and metadata, which you can then feed into other functions.
Can I find out what tasks need doing from a specific call using the Jiminny MCP? +
Yes. You use get_action_items on the relevant call ID. It strips away all filler and gives you only concrete next steps, like 'send proposal by Friday'.
What information does get_coaching_stats provide? +
get_coaching_stats delivers performance scores for a user. You'll get metrics like average call score and historical improvement trends.
Which tool should I use to check if Jiminny is connected? +
Use check_jiminny_status. This runs a simple verification that confirms the API connectivity before you attempt any complex data pulls.
How do I use the `get_transcript` tool to access a call's raw text? +
It returns the full, time-stamped conversation script. You can then send this text to your agent for further analysis or summarization. This lets you extract specific quotes or key discussion points that the other tools don't capture.
If I need a roster of staff, how do I use `list_users`? +
This tool returns a comprehensive list of all team members and their unique IDs. It’s crucial for ensuring you can accurately pull performance data or coaching stats for every individual on record.
What kind of high-level metrics does `get_call_stats` provide? +
It provides aggregate analytics across a defined set of calls, such as average call length or total volume. This lets managers quickly spot team trends and measure performance without having to review every single recording manually.
If I want general operational data, how does the `get_activity` tool help? +
This tool retrieves detailed records of specific interactions, including timestamps and participants. It's helpful for tracking recent actions or meetings that might not be part of a formal recorded call portfolio.
How do I access call transcripts via AI? +
Use the get_transcript tool with the activity ID to retrieve the full transcript with speaker identification and timestamps.
Can my agent extract action items from calls? +
Yes. Use get_action_items to retrieve all AI-detected follow-ups and tasks from any recorded conversation.
How do I review coaching metrics for my team? +
Use get_coaching_stats with the user ID to see call scores, framework ratings, and improvement trends for any team member.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.