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Connect Accelerator Peer Learning Value Engine to your AI

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Turn raw connections into actionable organizational intelligence.

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Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 3 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-03

3 capabilities in this set.

Part of 3 available through Accelerator Peer Learning Engine.

  1. 01

    Analyze knowledge flow

    This capability evaluates how structured events contribute to the overall network intelligence. It helps you understand the impact of specific workshops or programs on the cohort's collective knowledge base.

  2. 02

    Calculate peer learning metrics

    Use this capability to get a snapshot of the current network's health and connectivity. It provides key metrics that show how connected and dense the startup cohort actually is.

  3. 03

    Estimate collaboration value

    This capability translates network activity into a monetary value. It gives you an estimate of the economic utility derived from the cohort's interactions.

Real work

What teams actually run

01

Evaluating Program Success

After a major workshop, you run the MCP to see exactly how the new knowledge flow increased the overall network intelligence.

02

Due Diligence on Ecosystems

You analyze a potential investment sector by running the MCP to calculate the current peer learning metrics and overall connectivity.

03

Pitching Program Value

You use the collaboration value capability to show investors that the cohort's interactions are worth millions, not just a few meetings.

04

Optimizing Networking Events

You test different event structures by running the MCP to see which type of interaction yields the highest estimated collaboration value.

Automate a task

Put Accelerator Peer Learning Engine to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Accelerator Peer Learning Engine works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Accelerator Peer Learning Engine to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

867ms average. Fast in production.

Accelerator Peer Learning Engine is checked daily against the live service.

Daily averagePeak 1257ms
Oct 3Today
Fastest day
650ms
Slowest day
1257ms
14-day trend
Slowing+25%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 3 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Accelerator Peer Learning Engine, so you can see the experience inside your AI.

It does not authenticate your account with Accelerator Peer Learning Engine. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Accelerator Peer Learning Engine Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_U3JmniJruQZiDpBSxVUcoaax6WjyGyuLzlWRHwUa/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Accelerator Peer Learning Engine capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "accelerator-peer-learning-value-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_U3JmniJruQZiDpBSxVUcoaax6WjyGyuLzlWRHwUa/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Accelerator Peer Learning Engine in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Accelerator Peer Learning Engine owners hand off.

This MCP is essential for Venture Capitalists, Program Managers, and Startup Consultants. If your job involves measuring the return on investment (ROI) of networking events or accelerator programs, this capability is for you. It gives you the metrics needed to prove the value of the ecosystem.

  • 01

    Venture Capitalist

    Use it to quantify the structural value of a portfolio or cohort before making a follow-on investment.

  • 02

    Accelerator Program Manager

    Use it to prove the effectiveness of your program's events and connections to stakeholders.

  • 03

    Startup Consultant

    Use it to advise clients on how to structure their internal or external networks for maximum economic impact.

FAQ

Questions Accelerator Peer Learning Engine owners ask.

  • 01

    What kind of data does this MCP need to run?

    The MCP requires raw connection data, including details about the companies involved, and parameters like sector overlap and company maturity stages. The more detailed the input, the better the output.

  • 02

    Is this for all types of networks, or just startups?

    It is specialized for startup accelerator networks, but its core function is quantifying peer-to-peer learning and collaboration value within a defined cohort.

  • 03

    Can I tell if the connections are valuable enough for investment?

    Yes. By running the estimate_collaboration_value capability, you get a monetary figure that helps you assess the economic utility of the network's interactions.

  • 04

    Does this MCP just count connections?

    No. It goes far beyond counting. It calculates metrics like network density and analyzes how structured events boost knowledge flow, providing deeper insights.

  • 05

    Do I need to write code to use this MCP?

    No. You interact with this MCP through natural language prompts in your AI client. Your agent handles the capability invocation for you.

  • 06

    How does the engine calculate economic impact?

    The engine uses estimate_collaboration_value to sum the worth of individual collaborations, adjusting them by an outcome correlation factor and specific weights assigned to different company stages.

  • 07

    Can I measure the connectivity of my cohort?

    Yes, by using calculate_peer_learning_metrics, you can obtain the peer learning score and network density based on your cohort connections and sector overlap.

  • 08

    How are knowledge sharing events evaluated?

    The analyze_knowledge_flow capability evaluates how events act as catalysts for new connections and measures the resulting engagement index.

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