statefinance-mcp

by cstillick

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool serves a distinct purpose: donor history, candidate info, committee info, health check, contribution search, expenditure search, store stats, summary aggregates, and top donors. There is no ambiguity between them.
Naming Consistency2/5
Tool names mix verb-noun patterns (get_candidate, search_contributions) with noun phrases (donor_history, summary, ping) and inconsistent styles. This lack of a consistent pattern reduces predictability.
Tool Count5/5
With 9 tools, the set is well-scoped for a state finance data server. It covers essential queries without being overwhelming or too sparse.
Completeness4/5
The tools cover core workflows: lookup candidates, committees, donors, contributions, expenditures, and summaries. Minor gaps exist (e.g., no listing of all candidates or committees), but the surface is largely complete for a read-oriented server.
Average 3.2/5 across 9 of 9 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 7 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
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}
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
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 read-only nature, error handling (e.g., missing committee_id), rate limits, or idempotency. The phrase 'plus its contribution and expenditure totals' hints at the return structure but is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (one sentence), which is concise, but it sacrifices necessary detail. It is not structured with sections or examples, making it too terse for adequate understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no behavioral annotations, the description should provide more context about the response structure, possible values, or error conditions. It does not, leaving the agent with significant ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter 'committee_id' with 0% schema description coverage. The description adds no information about this parameter—no explanation of format, examples, or how to obtain it. This is a critical gap for a required parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clarifies that the tool returns not just a committee but also its contribution and expenditure totals, which distinguishes it from sibling tools like 'get_candidate' or search tools. However, it lacks an active verb like 'retrieve' and could be more explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'search_contributions' or 'summary'. The description does not specify context or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It mentions returned data (candidate info, committees, money) but omits crucial details like read-only nature, error conditions, authentication requirements, or side effects. The information is minimal and insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise. However, it contains inaccuracies and lacks detail, making it more under-specified than efficiently designed. It could be improved with clear, correct information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one required parameter, no output schema, and no annotations, the description is incomplete. It does not explain return format, pagination, or valid parameter values. The inaccuracy about the name parameter further reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds some meaning by stating the parameter identifies a candidate, but it inaccurately suggests a 'name' parameter exists, creating ambiguity. The description partially adds value but also misleads.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves a candidate (by id or name) along with their committees and financial data. It distinguishes from siblings like 'get_committee' which focuses solely on committees. However, the verb is implicit and not explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description mentions 'by id or name' but the schema only has a 'candidate_id' parameter, which is misleading and implies an additional parameter that does not exist.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only states what the output includes (totals and per-recipient breakdown), but does not disclose whether the operation is read-only, requires authentication, has rate limits, or how it handles missing donors. The behavioral information is minimal.
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?
The description is extremely concise (one sentence, 12 words) and front-loaded with the core purpose. However, its brevity comes at the cost of missing important details about parameters and usage, which slightly reduces the score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters, no output schema, and no annotations, the description is incomplete. It does not explain what the parameters mean, what the exact return format is, or how to interpret the 'totals' and 'per-recipient breakdown'. The description would be insufficient for an AI agent to use the tool correctly without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds no meaning to the three parameters. It does not explain that 'name' likely refers to the donor's name, nor does it clarify the purpose of 'cycle' and 'state' (e.g., election cycle, donor state). The description fails to compensate for the schema's lack of descriptions.
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: retrieving every contribution by a donor, with totals and per-recipient breakdown. It uses a specific verb (shows/retrieves) and identifies the resource (donor contributions). This distinguishes it from sibling tools like top_donors (which aggregates top donors) or search_contributions (which searches across contributions).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It does not specify that it is for looking up a specific donor's history, nor does it mention situations where other tools (e.g., search_contributions) would be more appropriate. No exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies read-only aggregation, but with no annotations to confirm, it fails to disclose safety guarantees, required permissions, or whether the tool is destructive. It also does not mention pagination, rate limits, or data freshness.
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?
The description is a single, front-loaded sentence that immediately conveys the tool's purpose. It is concise but lacks necessary details, which prevents a perfect score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and annotations, the description should explain what aggregated totals are returned (e.g., total contributions, total expenditures). It does not, nor does it address the meaning of 'cycle' or how results are structured.
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?
With 0% schema coverage, the description adds key meaning by listing possible scope_type values (committee, candidate, cycle). However, it does not clarify the format of scope_id (e.g., FEC ID, candidate ID, cycle year) or provide examples, leaving ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool aggregates totals for committee, candidate, or cycle resources. It uses specific verbs and resources, but does not distinguish from siblings like top_donors or get_candidate which may also provide summary-like data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as get_committee, get_candidate, or search_contributions. There is no mention of prerequisites or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral context about spelling variant normalization but lacks details on output format, pagination, rate limits, or being read-only. With no annotations, it partially fulfills transparency.
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?
A single sentence with no fluff, but could be better structured with parameter hints. However, it is concise and front-loaded with the main action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 3 undocumented parameters, no output schema, and no annotations, the description is insufficient for correct invocation. It lacks details on how to specify cycle or n, and what the return value contains.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% and the description provides no explanation of parameters (recipient, cycle, n). The agent must infer their meaning from names alone, which is insufficient.
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 returns top donors to a recipient committee, ranked by total given, with spelling normalization. It is specific and distinct from sibling tools like donor_history or search_contributions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives, prerequisites, or scenarios. The description only states what it does without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description indicates a read-only statistical operation. However, it doesn't disclose potential performance implications or whether counts are cached or real-time.
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?
The description is a single, efficient sentence that conveys the core purpose with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the zero-parameter schema and no output schema, the description is minimally adequate. It does not specify output format or structure, which could be inferred but not explicit.
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?
No parameters exist, so schema coverage is 100%. The description adds no parameter context, which is acceptable given zero parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides row counts for the normalized store, mentioning specific entities. It implicitly distinguishes from sibling tools that deal with individual records, but lacks explicit differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description provides no context for usage scenarios or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool returns 'matching contributions (each with source_url + as_of) plus the full-match count and total.' However, it does not mention any rate limits, authentication requirements, or side effects. For a read-only search, this is adequate but not comprehensive.
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?
Two sentences: the first lists search criteria, the second describes return fields. No redundant or irrelevant content. It is concise, though the complexity of 10 parameters might warrant slightly more structure (e.g., bullet points).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 10 optional parameters and no output schema, the description covers the core purpose and return format but omits details like pagination (limit parameter exists but no explanation), combination logic of filters, or data types. It is minimally complete for a search tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description lists the parameter categories (donor, recipient, etc.) in the first sentence, which adds context beyond the schema's plain titles, but does not explain formats or constraints (e.g., date format, state codes). With 10 parameters, more detail is needed for clarity.
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 uses the verb 'search' and specifies the resource 'campaign contributions' with multiple searchable criteria (donor, recipient, candidate, amount, date, state, cycle). It clearly distinguishes from sibling tools like get_candidate or donor_history, which retrieve individual entities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool—when searching for contributions by various filters—but does not explicitly state when not to use it or mention alternatives. No exclusions or prerequisites are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool returns expenditures with provenance plus count and total, which adds behavioral context beyond a basic search. However, it does not mention pagination, rate limits, or auth requirements.
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?
Two concise sentences front-loading the key filters and output. Every phrase is informative, and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 8 parameters with no schema descriptions and no output schema, the description adequately covers tool purpose, filters, and return values. It could mention pagination behavior for the limit parameter, but overall it is sufficient.
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 0% for 8 parameters, so the description must compensate. It lists the filter parameters in plain language but omits format details (e.g., date format, state codes) and constraints, leaving gaps for an agent.
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 specifies the verb 'search' and resource 'expenditures', listing multiple filter dimensions (committee, payee, purpose, date range, state, cycle) and output details (expenditures with provenance, count, total). This distinguishes it from sibling tools like search_contributions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by enumerating filters but does not explicitly state when to use this tool versus alternatives like search_contributions, nor does it provide exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states it returns 'pong' if alive, but does not disclose behavior on failure (e.g., error or timeout). However, for a simple health check, this is adequate given no annotations.
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 extremely concise with two short sentences, front-loading the purpose. Every word serves a purpose.
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 zero-parameter health check tool with an output schema, the description sufficiently covers purpose and return value. No additional information is necessary.
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?
There are no parameters and the schema is empty (100% coverage). The description adds no extra parameter information beyond what the schema provides, so baseline score 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?
The tool name 'ping' and description 'Health check' clearly indicate a connectivity test. No sibling tool serves a similar purpose, making its function unambiguous.
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 specifies the tool is for checking server liveness. Although no explicit alternatives or exclusions are given, the sibling tools are all data query tools, so the context strongly implies usage for verifying server status before other calls.
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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