civic-awareness-mcp
Server Quality Checklist
Latest release: v0.3.0
- Disambiguation4/5
Most tools have distinct purposes (bill detail, entity lookup, recent bills, votes, search, connections). However, search_civic_documents and recent_bills both retrieve bills, though via different access patterns (search vs. listing), causing minor overlap.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern using snake_case (e.g., get_bill, search_entities, recent_votes). No naming style conflicts.
Tool Count5/58 tools cover the domain of state legislative data without being too few or excessive. Each tool serves a clear function in the workflow.
Completeness4/5Core operations for browsing state bills, entities, votes, and connections are present. Missing features like jurisdiction listing or bill text retrieval are minor gaps that don't break typical workflows.
Average 3.6/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 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 failing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add
glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
Add related servers to improve discoverability.
How to sync the server with GitHub?
Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.
To manually sync the server, click the "Sync Server" button in the MCP server admin interface.
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?
With no annotations, the description must fully disclose behavior. It mentions confidence tiers and hydration but omits details on side effects, error states, permissions, or what happens with no matches. The behavior is only partially transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no redundancy. The first sentence states the core purpose, the second adds a key behavioral hint. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 4 parameters and no output schema, the description is incomplete. It lacks parameter docs for context and role_hint, does not describe the return format beyond confidence tiers, and omits error handling. More detail is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description should explain all parameters. It only describes name (implicitly) and jurisdiction_hint, leaving context and role_hint unexplained. This is insufficient for the 4-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'disambiguate' and the resource 'person by name across state legislators', distinguishing it from sibling tools like get_entity or search_entities. It also specifies return of matching Person entities with confidence tiers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a usage hint about jurisdiction_hint triggering upstream hydration but does not explicitly say when to use this tool over alternatives or when not to use it. No comparison to sibling tools is given.
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?
Discloses that votes are from recently-updated bills with embedded vote data and mentions local caching. However, no annotations are provided, and the description does not cover rate limits, authentication, or potential side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences that are front-loaded with the main purpose, no redundant or extraneous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 5 parameters and no output schema or annotations, the description lacks details on optional parameters, return format, and pagination. It only covers jurisdiction usage, leaving significant gaps for agent decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%. The description explains the jurisdiction parameter with examples but provides no information about the other four parameters (days, limit, chamber, session), leaving the agent to infer their meaning from the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists recent roll-call votes, specifies the data source (OpenStates), and gives jurisdiction examples. It is distinct from sibling tools like 'recent_bills'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides examples of jurisdiction input and mentions the wildcard '*' for all cached jurisdictions, but does not explicitly state when not to use this tool or suggest alternatives for other scenarios.
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 exist, so description must disclose behavior. It only states basic operation and optional filters, omitting details like pagination (limit param), result format, error handling, or rate limits. Fails to provide expected behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, 13 words, no redundancy. Front-loaded action and then optional filters. Very concise, though could benefit from listing filters if more detail needed. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 7 parameters, 100% undocumented in schema, and no output schema, the description is too minimal. It doesn't explain what the search returns, how results are ordered, or timeouts. A search tool requires more context for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Description maps 'date range' to from/to and lists filters (jurisdiction, kind, source), adding some meaning. But with 0% schema coverage, it should explain each parameter's valid values or constraints (e.g., no enums for jurisdiction/kinds/sources). Incomplete but partially helpful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it searches state civic documents (bills) by title, differentiating from siblings like get_bill (retrieves single bill) and recent_bills (lists recent). The verb 'search' and resource 'civic documents/bills' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Mentions optional filters (jurisdiction, kind, source, date range), giving context on when to apply them. Lacks explicit when-not or alternatives like 'use get_bill for a specific bill ID', but the context is clear enough.
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 mentions that passing jurisdiction triggers upstream hydration, but lacks details on read-only nature, result format, pagination, or error handling. This is insufficient for a search tool with 6 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at two sentences, with no filler. The first sentence clearly states the purpose, and the second adds a critical behavioral note. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of 6 parameters and no output schema or annotations, the description is incomplete. It covers only purpose and one parameter behavior, missing key aspects like pagination, default behavior without jurisdiction, and return type. Sibling tools do not compensate for this lack.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does 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 only hints at the meaning of 'q' (search by name) and 'jurisdiction' (triggers hydration), ignoring 'kind', 'limit', 'had_role', and 'had_jurisdiction'. This leaves 4 out of 6 parameters unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches for 'people or organizations by name across state legislatures', specifying the verb, resource, and context. It also distinguishes from sibling tools like get_bill or recent_bills which focus on bills, and the mention of OpenStates provides domain clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context that the tool is for searching entities by name, and hints at using 'jurisdiction' to trigger hydration, but does not explicitly state when not to use it or list alternatives. Sibling tools are available externally but not mentioned in the description.
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 defaults, override behavior, and the wildcard jurisdiction for local caching. However, it does not state that the operation is read-only, mention rate limits or authentication needs, or describe any side effects. This is adequate but leaves gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficient and front-loaded, starting with the core purpose. It packs multiple pieces of information into a single paragraph without fluff. Could be slightly more structured (e.g., use bullet points for filters), but it is concise and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and 13 parameters (31% coverage), the description provides good context for core functionality and use cases. However, it omits details about return format, pagination, error cases, and does not fully compensate for the low parameter coverage. It is functional but not fully complete for complex queries.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 31%, so the description must compensate. It lists many optional filters (chamber, session, subject, etc.) and explains `sponsor_entity_id` resolution and jurisdiction wildcard. However, it does not add detailed semantics for all 13 parameters (e.g., classification, `limit` behavior could be clearer). The description adds some value beyond the schema but is not comprehensive.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'U.S. state legislative bills from OpenStates', with details on defaults and optional filters. It distinguishes from siblings like get_bill (single bill) and recent_votes (votes) by focusing on recent bills, but does not explicitly contrast with all siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the default `days` parameter, how explicit date ranges override it, and mentions specific use cases like 'what did this legislator introduce'. It lacks explicit guidance on when not to use this tool versus alternatives, but the context is sufficient for an agent to infer appropriate usage.
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?
With no annotations, the description must carry the full behavioral burden. It honestly discloses that the tool returns edges capped at 100, sorted by co_occurrence_count, and supports depth 1 or 2. However, it does not state that the operation is read-only, mention any authentication needs, or describe behavior when no edges exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at three sentences, front-loaded with the core purpose. Every sentence adds essential information: what it does, depth options, and output constraints. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters, no output schema, and no annotations, the description covers key aspects but leaves gaps. It explains the output behavior (edges capped and sorted) but does not describe the response structure or fields. The 'min_co_occurrences' parameter is entirely omitted. Completeness is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% parameter descriptions, so the description must compensate. It explains the depth parameter and the edge cap/sorting, adding meaning beyond the schema's constraints. However, it fails to describe the 'id' parameter beyond 'entity ID' and does not mention the 'min_co_occurrences' parameter at all.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: returning co-occurrence edges to other entities via shared state bills, given an entity ID. It specifies depth options (direct or one hop) and output constraints (capped at 100, sorted by count). This distinguishes it from siblings like get_entity (which retrieves a single entity) and search_entities (which searches).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when an entity ID is available and edges are needed, but it lacks explicit guidance on when to use this tool versus alternatives like get_entity or search_entities. It does not mention prerequisites, limitations, or when not to use it.
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 full burden. It discloses that the operation fetches details (read) and lists included fields. However, it does not disclose limitations, error handling, or any side effects. For a read-only tool, this is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the core purpose and requirements. It is front-loaded with the action. It could be structured with bullet points for clarity, but it is already concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 3 required parameters and no output schema, the description provides the essential context (what it does and what it returns). However, it lacks details on parameter formats, output structure, and error behavior, leaving some uncertainty.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does 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 names the three required parameters but does not explain their meaning (e.g., jurisdiction format, session format, identifier format). The additional value over the schema is minimal.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Fetch full detail'), the resource ('a single state bill'), and the included fields ('actions, versions, sponsors, subjects'). It distinguishes from siblings like 'recent_bills' (list vs detail) and 'search_entities' (search vs fetch specific).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly requires 'jurisdiction, session, and identifier', indicating the parameters needed. It implies usage when needing detailed information on a specific bill, but does not explicitly state when not to use it or mention alternatives among siblings.
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 exist, so the description must convey behavior. It mentions returning recent related documents and a special case for state Persons, but omits disclosures about authentication, error handling, or read-only nature. Basic 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no filler. The main action is front-loaded, and the special case is appended efficiently. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple parameter set (single required string ID) and no output schema, the description covers the core functionality and a notable variant. Missing details on return format or error conditions, but adequate for a straightforward fetch.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no descriptions (0% coverage), but the description explains that the 'id' parameter is the entity identifier. This adds meaningful context beyond the schema's raw type definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Fetch', the resource 'a single entity', the method 'by ID', and includes specialized behavior for state Persons. It distinguishes well from siblings like get_bill or search_entities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when an entity ID is known but does not explicitly state when to use this tool versus alternatives (e.g., get_bill, resolve_person). No when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
GitHub Badge
Glama performs regular codebase and documentation scans to:
- Confirm that the MCP server is working as expected.
- Confirm that there are no obvious security issues.
- Evaluate tool definition quality.
Our badge communicates server capabilities, safety, and installation instructions.
Card Badge
Copy to your README.md:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/julianken/civic-awareness-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server