MCP Server Setup #

sfs-mcp exposes Scottfree Sports data as Model Context Protocol tools for AI assistants. Premium subscribers can ask an assistant for model research, current odds, line movement, historical results, summaries, betting-strategy leaderboards, public consensus, weather, scores, injuries, rosters, and prediction-market context.

The assistant supplies the reasoning and writing. Scottfree Sports supplies the data tools.

Access #

If you need Premium, view pricing.

Install #

The MCP server ships with the Python CLI package.

Requires Python 3.11 or newer:

python3 --version
python3 -m pip install --upgrade scottfree-sports-cli

Verify:

sfs --version
which sfs-mcp

Your Scottfree Sports API key should look like:

sk_alphapysports_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

Find it on the Account page:

https://sports-app.scottfreellc.com/app/account

What The MCP Server Can Do #

The server exposes 17 public customer tools.

Sports:

mlb, nba, nfl, nhl, ncaaf, ncaab

Model types:

over_under, won_on_points, won_on_spread

For moneyline and spread, probabilities are home-team relative. For over/under, probabilities are over-relative.

Tool Call Examples #

Your assistant calls tools for you. These examples show the exact argument shape each public tool expects.

get_daily_brief({"sport":"mlb"})

get_predictions({"sport":"mlb","model_type":"won_on_points"})

get_results({"sport":"mlb","model_type":"won_on_points","limit":25})

get_summary({"sport":"mlb","model_type":"won_on_points"})

get_strategies({"sport":"mlb","model_type":"won_on_points","season":"2026"})

get_odds({"sport":"mlb"})

get_sports({})

get_account_info({})

get_usage({})

get_kalshi_markets({"sport":"nfl"})

get_polymarket_odds({"sport":"nba"})

compare_market_odds({"sport":"mlb","model_type":"won_on_points"})

get_game_weather({"sport":"mlb"})

get_live_scores({"sport":"nba","date":"2026-05-23"})

get_injuries({"sport":"nba"})

get_players({"sport":"nba","search":"James","per_page":10})

get_betting_consensus({"sport":"mlb"})

Setup - Claude Desktop #

Claude Desktop runs local command MCP servers well.

1. Open Claude Desktop.
2. Go to Settings, Developer, Edit Config.
3. Add this server config:

{
  "mcpServers": {
    "scottfree-sports": {
      "command": "sfs-mcp",
      "env": {
        "SFS_API_KEY": "sk_alphapysports_PASTE_YOUR_KEY",
        "SFS_API_URL": "https://sports-api.scottfreellc.com"
      }
    }
  }
}

4. Fully quit and restart Claude Desktop.
5. Start a new chat and ask: "List the Scottfree Sports tools you can use."

If Claude Desktop cannot find sfs-mcp, use the full path:

which sfs-mcp

Then set:

"command": "/Users/you/.local/bin/sfs-mcp"

Config file locations:

Setup - Claude Code #

claude mcp add scottfree-sports sfs-mcp \
  --env SFS_API_KEY=sk_alphapysports_PASTE_YOUR_KEY \
  --env SFS_API_URL=https://sports-api.scottfreellc.com

Verify:

claude mcp list

Then start a new Claude Code session and ask:

Show me today's MLB moneyline model research and current odds.

Setup - Cursor Or Other Local MCP Hosts #

Use the same local command pattern:

{
  "mcpServers": {
    "scottfree-sports": {
      "command": "sfs-mcp",
      "env": {
        "SFS_API_KEY": "sk_alphapysports_PASTE_YOUR_KEY",
        "SFS_API_URL": "https://sports-api.scottfreellc.com"
      }
    }
  }
}

Some hosts require args instead of a single command. If so, use:

{
  "command": "python3",
  "args": ["-m", "sflow_cli.mcp_server"],
  "env": {
    "SFS_API_KEY": "sk_alphapysports_PASTE_YOUR_KEY",
    "SFS_API_URL": "https://sports-api.scottfreellc.com"
  }
}

Setup - ChatGPT #

ChatGPT custom MCP support is managed through OpenAI's app/connector flow and may require developer mode, workspace approval, or a remote MCP server. OpenAI's current help docs state that local MCP servers are not directly connected in ChatGPT; remote MCP or a supported tunnel/app flow is required.

Use Scottfree Sports with ChatGPT only if your ChatGPT plan and workspace support custom MCP apps/connectors. See OpenAI's docs:

• Apps in ChatGPT
• Developer mode and MCP apps in ChatGPT

For most customers today, Claude Desktop or Claude Code is the fastest path for local sfs-mcp.

Optional BALLDONTLIE Key #

The core Scottfree Sports tools do not require BALLDONTLIE. These tools do:

Configure:

sfs config set --balldontlie-api-key YOUR_BALLDONTLIE_KEY --use-keyring

If no BALLDONTLIE key is configured, those tools return a clear BALLDONTLIE API key not configured message instead of failing silently.

Tool Details #

get_daily_brief #

Parameters:

Returns a structured daily model brief across over/under and spread markets. Includes model pick labels, model probability, market-implied probability, signed Delta(Model-Implied), and model-position counts.

Good prompts:

Show me today's MLB daily brief. Sort the biggest model-vs-implied deltas first.

For tonight's NBA games, summarize where the model disagrees most with the market and explain what other context I should check.

get_predictions #

Parameters:

Returns current slate prediction rows and line fields.

Good prompts:

Get MLB moneyline predictions and explain the biggest difference between BLEND and IMPLIED.

Get NHL over/under predictions. For each game, show the over probability, implied probability, and current total.

get_results #

Parameters:

Returns recent graded result rows. Useful for checking whether a model has been running hot or cold recently.

get_summary #

Parameters:

Returns the summary table for all model columns, including win percentage and recent windows when available.

get_odds #

Parameters:

Returns current odds and line fields for the sport.

get_sports #

No parameters. Returns supported sports and model types.

get_account_info #

No parameters. Returns current account, plan, subscription status, and monthly limit.

get_usage #

No parameters. Returns monthly request count, limit, remaining requests, tier, and reset date.

get_kalshi_markets #

Parameters:

Returns Kalshi prediction-market data when available.

get_polymarket_odds #

Parameters:

Returns compact Polymarket event and market data.

compare_market_odds #

Parameters:

Returns Scottfree predictions, Kalshi markets, and Polymarket markets in one payload.

get_game_weather #

Parameters:

Best for outdoor sports: mlb, nfl, ncaaf.

get_live_scores #

Parameters:

Requires BALLDONTLIE key.

get_injuries #

Parameters:

Requires BALLDONTLIE GOAT tier.

get_players #

Parameters:

Requires BALLDONTLIE key.

get_betting_consensus #

Parameters:

Returns public betting consensus from Covers.

Example Premium Session #

Try this sequence in Claude Desktop or Claude Code:

You are helping me research today's MLB slate. Use Scottfree Sports tools only as data sources. Do not invent missing data.

1. Call get_daily_brief for MLB.
2. Call get_predictions for MLB moneyline.
3. Call get_odds for MLB.
4. Call get_summary for MLB moneyline.
5. If useful, call get_betting_consensus and get_game_weather.
6. Present a table with game time, matchup, current line, BLEND probability, IMPLIED probability, Delta(Model-Implied), and any notable context.
7. Separate model disagreement from betting recommendation. Tell me what is data-backed and what is uncertain.

For multi-tool examples, see MCP Workflows. For a longer walkthrough, see the Premium MCP Demo.

Troubleshooting #

sfs-mcp: command not found #

Install or upgrade:

python3 -m pip install --upgrade scottfree-sports-cli

Then locate it:

which sfs-mcp

Use the full path in your MCP config if your assistant cannot find it.

The server starts but every tool returns 401 #

The API key is missing, revoked, expired, or copied incorrectly. Verify in a terminal:

SFS_API_KEY=sk_alphapysports_PASTE_YOUR_KEY sfs account info

The server starts but tools return 403 #

Your key is valid but the subscription tier does not allow MCP. MCP is Premium-only.

Claude Desktop does not show the tools #

Fully quit and restart Claude Desktop. On macOS, use Cmd+Q; closing the window is not enough.

Scores or injuries fail #

Core Scottfree tools should still work. Scores, players, and injuries use BALLDONTLIE and need your own BALLDONTLIE key. Injuries require their GOAT tier.

Answers feel stale #

Predictions refresh after scheduled pipeline runs. Ask the assistant to call get_predictions, then inspect the predictions_date field.

See Also #

• CLI Reference
• API Reference
• Premium MCP Demo
• Account Page