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FPL MCP

FPL MCP

by MoayadAbbara
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

login_to_fpl

Authenticate to Fantasy Premier League by opening a real browser for manual sign-in, then capture and store the session token for subsequent actions.

Instructions

Open a browser to sign in to Fantasy Premier League and save the token.

A real browser window opens on the FPL site. The user signs in there themselves; their password is never seen by this tool or the model. Once signed in, the session token is captured and stored for later calls.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "login_to_fpl"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description fully discloses the tool's behavior: it opens a real browser window, requires the user to sign in manually, ensures the password is never seen by the tool or model, and captures the session token for later calls. This transparency is exceptional, leaving no hidden side effects or surprises.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, consisting of two short sentences. The first sentence states the primary purpose, and the second elaborates on the process, including security aspects. There is no redundant information, and the structure is front-loaded with the key action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description provides sufficient context for an agent: it explains the user interaction, the security guarantee, and the outcome (token storage). Since an output schema exists, there is no need to describe return values. The description covers all necessary aspects for correct invocation and expectation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are no parameters in the input schema, so the description does not need to explain any. The schema coverage is effectively 100% because there are no parameters to document. The description appropriately focuses on the process and outcome rather than parameter details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: it opens a browser to sign in to Fantasy Premier League and saves the token. The verb 'open' and the resource 'Fantasy Premier League' are specific, and the outcome (saving the token) is unambiguous. It is distinct from sibling tools which focus on data retrieval or actions after authentication.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies that this tool should be used before other calls that require authentication, as it stores a token for later use. However, it does not explicitly state when to use it in relation to alternatives or provide a when-not scenario. The guidance is clear enough for an agent to infer the proper sequencing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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