The uDocit MCP Server: Your IDE is now Project Aware

The biggest bottleneck in AI-assisted coding isn't generating code—it's context.

When you ask an AI to "implement the login page," it doesn't know about your design system, your user roles, or the acceptance criteria you wrote last week. You waste time copy-pasting spec docs into chat windows, only to have the model forget them ten messages later.

This "Context Gap" leads to hallucinated requirements and code that doesn't fit the spec.

Today, we're solving this with the uDocit MCP Server.

What is MCP?

The Model Context Protocol (MCP) is an open standard that lets AI models talk to your data. Think of it like a USB port for AI context.

Instead of manually feeding your specs to an AI, you "plug in" uDocit to your agent. Your agent then gains the ability to pull fresh data from your project whenever it needs it.

This connection fundamentally changes the workflow:

1. You write specs in uDocit (User Stories, Personas, Features).
2. You code in VS Code / Cursor.
3. Your agent bridges the two.

Why Connect Your IDE?

Once connected, your coding assistant becomes a Product Manager. It can read your stories, check your timeline, and even track your work—all without you leaving VS Code.

1. Zero-Hallucination Implementation

Stop guessing what the "Admin" user type is allowed to do.

User: "Write the auth middleware for the Admin user."

Without MCP, the AI guesses standard admin permissions. With MCP, the agent queries get_user_types:

Agent: "Based on your spec, the Admin has manage_users and view_reports access, but I've explicitly blocked delete_projects as per the security requirements."

The code matches your spec 100%.

2. Bi-Directional Status Updates

Finished a story? Don't alt-tab to Jira or Linear. Just tell your agent.

User: "I finished the 'Login' story."

Agent: "Scanning stories... Found Story #4 'User Login'. Marking criteria 1-4 as passed. Project progress updated to 15%."

3. Smart Time Tracking & Auto-Calibration

This is where it gets magic. When you log work via MCP, uDocit compares your actual time vs. your estimated time.

• You estimate: 4 hours
• You log: 3 hours (via agent)
• uDocit records: -25% variance

If you consistently complete "High Complexity" tasks faster than estimated, uDocit learns. The next time you plan a sprint, it will suggest tighter estimates based on your real velocity.

Under the Hood: The Tools

We expose a rich set of tools to your agent. Here are a few key ones:

How to Set It Up

We've made it incredibly easy. Go to Settings > MCP in your uDocit dashboard.

{
  "mcpServers": {
    "udocit": {
      "url": "https://udocit.com/api/mcp/mcp",
      "headers": {
        "Authorization": "Bearer mcp_..."
      }
    }
  }
}

1. Create a Key: Generate a new API key (Read-only or Read/Write).
2. Copy Config: We provide one-click configuration snippets for Cursor, VS Code, and Claude.
3. Chat: Your agent is now context-aware.

Real-World Scenario: The "Context-Aware" Refactor

Imagine you need to refactor a payment flow.

Without MCP:

1. Read the old code.
2. Search Slack/Docs for why it was written that way.
3. Hope you don't break a requirement you forgot about.

With uDocit MCP: You simply ask: "Check the 'Payment Flow' story constraints and tell me if removing the phone number field violates any requirements."

Your agent checks get_stories and get_test_cases instantly:

"Yes, it violates Requirement #3.1: 'For fraud prevention, a verified phone number is required before transaction'."

You just saved a bug from hitting production.

Try it today

The MCP Server is available now for all Pro users. Stop context switching and start coding with a partner that actually knows your project.

Get your API Key →