SiteCheck Crypto & Finance

US federal campaign contributions from the official OpenFEC

finance_fec_campaign_finance_contributions

Read-only

US federal campaign contributions (FEC Schedule A itemized receipts) from the official OpenFEC API, by contributor name, employer, committee ID or state for a two-year cycle: contributor, employer, occupation, city/state/ZIP, amount, date, committee, receipt type, memo and filing image link, newest first, with total count. FEC law forbids using contributor names for solicitation or commercial purposes. Price: $0.002 in USDC per successful call, paid with x402 (Base, Solana or Arc); failed calls are not charged.

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": "finance_fec_campaign_finance_contributions"
  }
}

Input Schema

Name	Required	Description
`cycle`	No	Two-year period ending year, e.g. 2024 (default: current cycle)
`limit`	No	Results, 1 to 100 (default 20)
`state`	No	Contributor state, e.g. MD
`employer`	No	Contributor employer, e.g. NASA
`minAmount`	No	Minimum amount in USD
`committeeId`	No	Receiving committee ID, e.g. C00703975
`contributor`	No	Contributor name, e.g. Bezos (name searches can take ~20 s at FEC)

Output Schema

Name	Required	Description	Default
`cycle`	No
`total`	No
`source`	No
`keyUsed`	No
`checkedAt`	No
`contributions`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 23, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Beyond the readOnlyHint/openWorldHint annotations it discloses cost ($0.002 USDC per successful call, failed calls free), the x402 payment rails (Base, Solana, Arc), result ordering (newest first with total count), and a legal usage restriction on contributor names. That is exactly the kind of operational and compliance context the annotations cannot express.

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

Conciseness4/5

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

Front-loads the resource and filters, then tacks on compliance and pricing in two short sentences. The opening sentence is long and enumerates return fields (contributor, employer, occupation, city/state/ZIP, amount...) that an output schema already covers, which is mild redundancy.

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?

For a payment-gated, open-world data lookup, the description covers what is queried, how results are ordered, what the call costs, and the legal limits on use; return-shape details are delegated to the output schema. Nothing an agent needs before invoking it is missing.

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

Parameters3/5

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

Schema description coverage is 100%, so every parameter including the ~20 s name-search latency caveat is already documented in the schema. The description only restates the filter axes as prose and adds no syntax or constraint detail beyond it, so the baseline 3 applies.

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?

States a specific resource (US federal campaign contributions, FEC Schedule A itemized receipts) and the source (official OpenFEC API), plus the slicing keys. An agent can tell instantly this is a political-contribution dataset tool, distinct from every crypto/market sibling in the list.

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?

It names the four query axes (contributor name, employer, committee ID, state) and the cycle granularity, which tells the agent how to frame a lookup. It does not state exclusions or point at any alternative tool, but no sibling here overlaps this dataset, so the gap is minor.

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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