FEC Campaign Finance
Server Details
FEC campaign finance data: candidate fundraising, donors, and spending
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 3.7/5 across 3 of 3 tools scored.
Each tool targets a distinct entity: candidates (fundraising totals), donors (individual contributions), and spending (expenditures). No overlap in purpose.
All tools follow the consistent 'get_fec_{noun}' pattern, using snake_case and plural nouns, making them predictable.
Three tools cover the core data types for FEC campaign finance, which is slightly minimal but adequate for a focused server.
The server covers candidates, donors, and spending, but lacks tools for committees, filings, or detailed reporting, though the main queries are addressed.
Available Tools
3 toolsget_fec_candidatesAInspect
Get FEC campaign finance data for federal election candidates. Returns fundraising totals, cash on hand, and spending by office (President/Senate/House), state, or party.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Candidate name search | |
| limit | No | Number of results (max 50) | |
| party | No | DEM, REP, IND | |
| state | No | 2-letter state code (TX, CA, NY) | |
| office | No | P=President, S=Senate, H=House | |
| election_year | No | Election cycle year (default: 2026) | 2026 |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. States what data is returned but does not explicitly state it is read-only, mention authentication needs, or rate limits. Acceptable but could be more transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-loaded with verb 'Get' and resource. No wasted words, immediately actionable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 optional parameters, no output schema, and no annotations, the description covers inputs and outputs well. Lacks mention of authentication or read-only nature, but is largely complete for a data retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with clear per-parameter descriptions. The tool description adds context about return types but does not significantly enhance individual parameter meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it gets FEC campaign finance data for candidates, specifies return data types (fundraising, cash on hand, spending) and filtering dimensions (office, state, party). Distinct from siblings which focus on donors and spending.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage for candidate-level data but lacks explicit when-to-use or when-not-to-use guidance. No mention of alternatives like get_fec_donors or get_fec_spending.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_fec_donorsBInspect
Get individual donor/contribution data for a candidate or committee from FEC Schedule A filings. Find who is funding campaigns.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of results | |
| state | No | Donor state filter | |
| employer | No | Donor employer to search (e.g. "Google", "Goldman Sachs") | |
| min_amount | No | Minimum donation amount | |
| candidate_id | No | FEC candidate ID (e.g. P80001571) | |
| committee_id | No | FEC committee ID (e.g. C00703975) | |
| election_year | No | Election cycle (default: 2026) | 2026 |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only indicates a read operation ('Get...'), but omits any details about authentication, rate limits, data freshness, or potential errors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no redundant words, front-loaded with the core action. Every sentence is necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 7 parameters, no output schema, and no annotations, the description is too minimal. It does not explain return format, parameter interactions, or typical usage patterns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds no additional parameter context beyond the schema's own descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves individual donor/contribution data from FEC Schedule A filings, distinguishing it from sibling tools for candidates (get_fec_candidates) and spending (get_fec_spending).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing donor information ('Find who is funding campaigns'), but lacks explicit when-to-use, when-not-to-use, or alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_fec_spendingAInspect
Get campaign spending data. Type=independent for Super PAC / outside group spending for/against candidates. Type=expenditures for direct campaign spending.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | independent (Super PAC spending) or expenditures (campaign disbursements) | independent |
| limit | No | Number of results | |
| candidate_id | No | Filter by candidate ID | |
| committee_id | No | Committee ID (required for type=expenditures) | |
| election_year | No | Election cycle (default: 2026) | 2026 |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as whether the operation is read-only, any authorization requirements, rate limits, or pagination behavior. While 'Get' implies a read operation, explicit transparency is lacking.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with three sentences. The first sentence states the purpose, and the next two explain the key parameter. No redundant information, and the most important details are front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters, all described in schema with added context from description, and no output schema, the description covers the essential usage. However, it does not mention the structure of the returned data, which could be helpful for a data retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with all parameters described, but the description adds value by explaining the meaning of the 'type' parameter values and clarifying that 'committee_id' is required for 'expenditures'. This goes beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get campaign spending data' and differentiates between 'independent' and 'expenditures' types. This distinguishes it from sibling tools (get_fec_candidates, get_fec_donors) which focus on other aspects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use each type value ('independent' for Super PAC spending, 'expenditures' for direct spending) and notes that committee_id is required for 'expenditures'. However, it does not explicitly exclude use cases or compare with sibling tools.
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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