> ## Documentation Index
> Fetch the complete documentation index at: https://rekko.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# MCP Trading Workflow

> Use Rekko's MCP server to research prediction markets from your AI coding assistant. Install rekko-mcp, browse markets, run deep analysis, find arbitrage, and manage a portfolio — all via natural language.

```bash theme={null}
# Install in one command
uvx rekko-mcp
```

## What this page covers

* What MCP is and why it matters for prediction market research
* Installing and configuring `rekko-mcp` for Claude Code and Cursor
* Workflow examples: screening, analysis, arbitrage, portfolio
* Available MCP tools (25+)
* When to use MCP vs the REST API

***

## What is MCP?

The Model Context Protocol (MCP) lets AI coding assistants call external tools during a conversation. Instead of copy-pasting API calls, you describe what you want in natural language and the assistant uses the right API endpoints automatically.

Rekko's MCP server (`rekko-mcp`) exposes 25+ tools covering market data, deep analysis, trading signals, arbitrage detection, and portfolio management. Your AI assistant calls these tools behind the scenes while you focus on the research question.

## Installation

### Requirements

* Python 3.10+
* A Rekko API key ([sign up free](https://rekko.ai/dashboard))

### Claude Code

<CodeGroup>
  ```bash Plugin install (recommended) theme={null}
  claude plugin install rekko
  ```

  ```json Manual .mcp.json theme={null}
  {
    "mcpServers": {
      "rekko": {
        "command": "uvx",
        "args": ["rekko-mcp"],
        "env": {
          "REKKO_API_KEY": "rk_free_your_key_here"
        }
      }
    }
  }
  ```
</CodeGroup>

### Cursor

Create or edit `.cursor/mcp.json` in your project root:

```json theme={null}
{
  "mcpServers": {
    "rekko": {
      "command": "uvx",
      "args": ["rekko-mcp"],
      "env": {
        "REKKO_API_KEY": "rk_free_your_key_here"
      }
    }
  }
}
```

### Verify installation

Ask your assistant: "List the top 5 prediction markets by volume." If `rekko-mcp` is configured correctly, it will call the `list_markets` tool and return formatted results.

## Workflow examples

### 1. Market screening

**You say:** "Find Kalshi markets with high volume that might have mispriced odds."

**What happens behind the scenes:**

1. Assistant calls `list_markets(source="kalshi", limit=20)` to fetch active markets
2. Calls `screen_markets(...)` to score them by volume, movement, and category
3. Presents the top candidates with scores and recommended actions

**Example output:**

```
Top Kalshi markets by opportunity score:

1. KXFED-26APR30 — "Fed rate decision April 2026"
   Score: 82 | Volume: $1.2M | Action: analyze

2. KXBITCOIN-26APR — "Bitcoin above $150K by April?"
   Score: 74 | Volume: $890K | Action: analyze

3. KXINFLATION-26MAY — "CPI above 2.5% in May?"
   Score: 68 | Volume: $540K | Action: watch
```

### 2. Deep analysis

**You say:** "Analyze the Fed rate decision market on Kalshi. I want to understand the key factors driving the price."

**What happens:**

1. Calls `analyze_market(bet_text="Fed rate decision April 2026", platform="kalshi")`
2. Returns an `analysis_id` — the research pipeline takes 30-90 seconds
3. Polls `check_analysis_status(analysis_id)` until complete
4. Retrieves the full analysis with probability, confidence, edge, key factors, and risks

**Example output:**

```
Analysis complete for KXFED-26APR30:

Probability: 71% (market: 62%) — Edge: +9 points
Confidence: 82% | Risk: low
Recommendation: BUY YES

Key factors:
- PCE inflation at 2.1% — within Fed's comfort zone
- Three FOMC members signaled openness to cuts
- Jobless claims trending upward (225K → 238K)

Risks:
- Strong employment report could reverse dovish signals
- Tariff escalation could reignite inflation expectations

Sources analyzed: 14
```

### 3. Arbitrage hunting

**You say:** "Are there any arbitrage opportunities between Kalshi and Polymarket right now?"

**What happens:**

1. Calls `get_arbitrage(min_spread=0.02)` for cached results (instant)
2. If you ask for fresh data, calls `get_arbitrage_live(min_spread=0.02)` (10-30 seconds)
3. Returns matched events with spreads, scores, and which platform is cheaper

### 4. Portfolio management

**You say:** "Show my shadow portfolio and suggest what to do next."

**What happens:**

1. Calls `get_portfolio(mode="shadow")` to list open positions
2. Calls `get_performance(mode="shadow")` for aggregate stats
3. May call `check_resolutions()` to settle any resolved markets
4. Presents positions, P\&L, win rate, and suggestions

### 5. Trading signals

**You say:** "Should I buy the Bitcoin $150K market? I have a $10K bankroll and already hold positions in the Fed rate market."

**What happens:**

1. Calls `get_portfolio_strategy(...)` with your current positions and bankroll
2. Returns a portfolio-aware signal accounting for correlation between positions
3. Includes Kelly-optimal size, hedge recommendations, and concentration warnings

### 6. Market data refresh

**You say:** "Refresh the Kalshi market data."

**What happens:**

1. Calls `run_scraper(platform="kalshi")` to pull the latest markets
2. Fresh data is available for subsequent queries

## Available tools

### Market intelligence

| Tool                     | Description                               |
| ------------------------ | ----------------------------------------- |
| `list_markets`           | Browse active markets, filter by platform |
| `get_market`             | Get a single market with pricing data     |
| `search_markets`         | Search markets by text query              |
| `get_market_history`     | Price and volume history (48h, 7d, 30d)   |
| `get_resolution`         | Resolution timing and mechanism           |
| `get_execution_guidance` | Optimal trade execution analysis          |

### Screening and discovery

| Tool              | Description                                          |
| ----------------- | ---------------------------------------------------- |
| `screen_markets`  | Batch score markets with volume and movement filters |
| `get_calibration` | Signal accuracy metrics (free, no auth)              |

### Deep research

| Tool                    | Description                                 |
| ----------------------- | ------------------------------------------- |
| `analyze_market`        | Trigger a deep AI analysis pipeline (async) |
| `check_analysis_status` | Poll analysis progress                      |
| `get_analysis`          | Retrieve completed analysis                 |
| `list_analyses`         | Browse recent analyses                      |

### Strategy and portfolio

| Tool                     | Description                                      |
| ------------------------ | ------------------------------------------------ |
| `get_strategy`           | Trading signal with Kelly sizing (blocks 30-90s) |
| `get_portfolio_strategy` | Portfolio-aware signal with correlation          |
| `get_consensus`          | Aggregated agent consensus probability           |

### Arbitrage

| Tool                 | Description                         |
| -------------------- | ----------------------------------- |
| `get_arbitrage`      | Cached cross-platform opportunities |
| `get_arbitrage_live` | Fresh scan (10-30 seconds)          |

### Correlation

| Tool              | Description                       |
| ----------------- | --------------------------------- |
| `get_correlation` | Cross-market correlation analysis |

### Trading

| Tool                 | Description                              |
| -------------------- | ---------------------------------------- |
| `place_shadow_trade` | Paper trade for tracking                 |
| `report_trade`       | Report a trade for consensus aggregation |
| `get_portfolio`      | Current positions and P\&L               |
| `get_performance`    | Win rate, ROI, and edge metrics          |
| `check_resolutions`  | Settle resolved markets                  |

### Data refresh

| Tool          | Description                         |
| ------------- | ----------------------------------- |
| `run_scraper` | Refresh market data from a platform |

### Webhooks

| Tool             | Description            |
| ---------------- | ---------------------- |
| `create_webhook` | Register event webhook |
| `list_webhooks`  | List your webhooks     |
| `delete_webhook` | Remove a webhook       |

## MCP vs REST API

| Scenario                            | Use MCP | Use REST API |
| ----------------------------------- | ------- | ------------ |
| Interactive research in your IDE    | Yes     |              |
| Automated trading bot               |         | Yes          |
| Quick market check during coding    | Yes     |              |
| Production pipeline                 |         | Yes          |
| Portfolio review                    | Yes     |              |
| Webhook/streaming integration       |         | Yes          |
| One-off analysis during development | Yes     |              |
| Scheduled batch processing          |         | Yes          |

MCP is ideal for exploratory research and ad-hoc queries. The REST API is better for automated systems that run without human interaction.

## Tips for effective MCP usage

**Be specific about platforms.** "Show me Kalshi markets" is faster than "show me markets" because the tool skips Polymarket data.

**Request expansions explicitly.** "Analyze this market and show me the causal factors" triggers the `?expand=causal` parameter automatically.

**Chain analyses.** "Analyze the top 3 markets from that screening" works — the assistant remembers prior results and makes sequential tool calls.

**Use shadow trading.** "Place a shadow trade on the Fed market, \$500 on YES" lets you track performance without risking real money.

## What's next

<CardGroup cols={3}>
  <Card title="MCP tools reference" icon="list" href="/docs/integrations/mcp/tools-reference">
    Full parameter documentation for all 25+ tools.
  </Card>

  <Card title="Build a trading bot" icon="robot" href="/docs/guides/build-trading-bot-python">
    When you are ready to automate, use the REST API.
  </Card>

  <Card title="REST API quickstart" icon="rocket" href="/docs/quickstart">
    Get an API key and make your first call in 5 minutes.
  </Card>
</CardGroup>