Getting Started with MCP Tools: 63 Ways to Supercharge Claude Code

The Model Context Protocol (MCP) is an open standard that lets AI assistants connect to external tools and data sources. Think of it as a USB port for AI — plug in a tool, and your AI agent gains new capabilities without any custom integration code.

Sprintra ships with 17 consolidated MCP tools (covering 70+ operations via method dispatch) that transform Claude Code from a capable code generator into a full-stack project management partner. Here's how to set it up and the workflows that will change how you build software.

Setting Up in 60 Seconds

If you're using Sprintra Cloud, generate an MCP token from your dashboard and add this to your Claude Code config:

{
  "mcpServers": {
    "sprintra": {
      "url": "https://api.sprintra.io/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_TOKEN"
      }
    }
  }
}

For self-hosted mode, the setup is even simpler:

{
  "mcpServers": {
    "sprintra": {
      "command": "npx",
      "args": ["sprintra", "mcp"]
    }
  }
}

Restart Claude Code, and you'll see 63 new tools available. You don't call them directly — just talk to Claude naturally, and it invokes the right tools automatically.

The Five Essential Workflows

1. Project Bootstrap

Start by creating a project. Open Claude Code in your repo directory and say:

Claude calls create_project with your tech stack metadata and links it to your repository path. From now on, every MCP call from this directory automatically targets this project — no project ID needed.

2. Feature Planning

When you're ready to plan work, describe what you want to build:

Claude creates a feature with acceptance criteria, then generates stories for each piece of work. Each entity gets a completeness score — a three-tier indicator (green/yellow/red) that shows how well-defined it is. If the score is low, Claude will try to fill in missing details from the conversation rather than asking you to repeat yourself.

3. Session Continuity

This is where Sprintra really shines. At the start of every coding session, your AI agent automatically:

1. Calls get_active_session to check if a previous session exists
2. If resuming, loads the context from the last session
3. If starting fresh, calls start_work_session
4. Calls get_next_work to see the recommended next task

At the end of the session, it saves what was accomplished, which files changed, and what to do next. The next session picks up right where you left off — even if it's a completely new conversation with no shared context.

4. Decision Recording

Every technical discussion that produces a decision should be captured:

This creates an Architecture Decision Record (ADR) with three parts: context (what led to the decision), decision (what was decided), and consequences (what this means going forward). When future sessions encounter related questions, they check existing decisions first.

5. Git Integration

After a coding session, sync your commits to Sprintra:

Sprintra imports commit metadata and associates it with features. The dashboard then shows AI authorship percentage — how much of each feature was written by AI vs human developers. This isn't about surveillance; it's about understanding your team's development patterns.

Tool Categories at a Glance

The 17 consolidated tools use a method dispatch pattern — each tool groups related operations:

Beyond Claude Code

While Sprintra is optimized for Claude Code, MCP is an open standard. The same tools work with Cursor, Windsurf, and any editor that supports MCP. The cloud version uses HTTP transport, while self-hosted uses stdio — both expose the same 17 consolidated tools. Plus, Sprintra offers agent-optimized REST endpoints (/api/agent/context and /api/agent/next-work) that deliver full project context in a single API call.

Everything your AI agent creates is visualized in the Sprintra dashboard — a React-based interface with 20+ views including Kanban boards, burndown charts, dependency graphs, and knowledge base management.