civicgraph-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 targets a distinct operation on the graph: querying connections, entity details, paths, stats, health, resolution, and search. No overlapping purposes.
Naming Consistency5/5
All tool names follow a consistent lower_snake_case pattern (e.g., entity_profile, resolve_entity, path_between). No mixing of styles.
Tool Count5/5
Seven tools is appropriate for a graph querying server, covering search, resolution, profiling, connection traversal, path finding, stats, and health checks without being excessive.
Completeness4/5
The tool set covers core graph exploration needs, but lacks direct listing of all entities or raw edge retrieval. Minor gaps, but main workflows are supported.
Average 3.7/5 across 7 of 7 tools scored. Lowest: 3.1/5.
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.
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.
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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 provided, so description bears full burden. Only states 'shortest sourced path' without disclosing behavior like cost, limits, or whether it's read-only. Lacks important context for agent decision-making.
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?
Single sentence that is front-loaded with verb and core purpose. No wasted words; every part adds value.
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 annotations, the description is incomplete. It lacks parameter explanations, output format, and any constraints or nuances (e.g., what 'sourced' means, types of connections). Minimal context for a tool with 3 parameters.
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 description adds no explanation for any of the 3 parameters (entity_a, entity_b, max_hops). The default for max_hops (4) is not explained. Agent receives no help understanding parameter semantics.
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?
Description clearly states verb (finds), resource (shortest sourced path between two entities), and scope (money/influence connections). Distinguishes from siblings like 'entity_profile' which focuses on a single entity.
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?
Implies usage for finding shortest path in network, but no explicit guidance on when to use this vs siblings like 'connections' or 'graph_stats'. No contraindications provided.
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 disclose behavior. It reveals hop distance and filtering by types, but does not specify whether all neighbors are returned at once, ordering, or performance characteristics. The behavior is partially transparent but not fully detailed.
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?
A single, concise sentence of 19 words that efficiently conveys the core functionality. No unnecessary words, and the main action is front-loaded.
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 tool has 3 parameters and no output schema or annotations, the description provides a reasonable overview but lacks details on output and parameter descriptions for entity_id. It is somewhat incomplete for a graph traversal 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 coverage is 0%, so the description must explain parameters. It explains 'hops' and 'types' (listing allowed values), but does not describe 'entity_id' at all. The explanation of 'types' is basic and doesn't clarify array format.
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 indicates the tool retrieves neighboring entities within a given number of hops, optionally filtered by edge types. However, it does not explicitly state the output format or use a strong verb like 'get' or 'retrieve'.
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 for exploring connections, but provides no explicit guidance on when to use this tool versus siblings like path_between or entity_profile. No exclusion criteria or alternatives are mentioned.
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 provided, so the description must carry the behavioral disclosure burden. It does not mention whether the operation is read-only, if it requires special permissions, or any performance implications. The focus is on content, not behavior.
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?
A single, well-structured sentence that front-loads the purpose ('Everything we know about an entity') and follows with specific contents. No wasted 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?
The description outlines the tool's output (aliases, sources, edges) but lacks specifics on return format, pagination, or limits. Without an output schema, more details would help, though the summary is adequate for basic use.
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?
The only parameter 'entity_id' is not described in the tool description. With 0% schema description coverage, the description should compensate but it does not. However, the parameter name and required nature make its purpose somewhat clear, meriting a score of 3.
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 it provides 'everything we know about an entity' including aliases, sources, and edges summarized by type with provenance. This is a specific verb-resource combination that distinguishes it from siblings like 'connections' or 'resolve_entity'.
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?
Implied usage: use when you need a comprehensive profile of an entity. However, it does not explicitly state when not to use it or provide comparisons to sibling tools, leaving some ambiguity.
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 implies a read-only operation ('Row counts'). However, it does not disclose potential performance impact, whether counts are cached, or if any side effects exist. The description is minimal but adequate for a simple stat tool.
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 a single sentence that efficiently communicates the tool's purpose. No extraneous information or repetition.
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?
The description does not specify the output format or structure (e.g., JSON object with keys). Given no output schema, a more detailed explanation of the return value would enhance completeness. Current description is functional but leaves ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, and the input schema is empty. The description adds no extra meaning since there are no parameters. Baseline 4 applies due to zero parameters and full schema coverage.
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 provides row counts for the graph store, listing specific categories (nodes, edges, entities). It distinguishes from sibling tools which perform different operations like path finding or entity resolution.
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 its siblings. The description lacks context on use cases, prerequisites, or scenarios where alternatives like 'connections' or 'entity_profile' are more appropriate.
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 mentions 'ranked by similarity', which gives some insight into the behavior, but lacks details on case sensitivity, partial matching, or ranking algorithm. Since no annotations exist, the description carries full burden but is only moderately transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no superfluous words, making it highly concise and efficient.
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?
For a simple tool with two parameters and no output schema, the description covers the core functionality adequately. It could mention the scope (entity names and aliases) and ranking, but doesn't need more details.
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?
The description adds meaning to the 'query' parameter by clarifying it searches entity names and aliases. The 'limit' parameter remains unexplained, but its purpose is fairly obvious. Given 0% schema coverage, the description provides partial compensation.
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 explicitly states 'Full-text search across entity names and aliases', which specifies the action (search) and the resource (entity names and aliases). This clearly differentiates it from sibling tools like 'connections' or 'entity_profile'.
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 for searching entities by name, but provides no explicit guidance on when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites.
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, the description discloses key behaviors: returns best match with confidence score, driving features, runner-up alternatives, and promises no silent merge. This is transparent for a read-like resolution tool, though no side-effect details are needed.
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 sentences, front-loaded with the core action. Every part adds value: the verb, resource, hint role, and return structure. No fluff.
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?
For a resolution tool with 4 parameters and no output schema, the description covers purpose, parameter roles, and return structure (confidence, features, alternatives). Lacks error handling or edge cases, but overall adequate.
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 coverage is 0%. The description mentions optional hints (state, employer, kind) disambiguate but provides no constraints, valid values, or examples. The 'name' parameter gets minimal context. This adds little beyond parameter names.
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 a specific verb 'Resolve' and resource 'name/organization to a canonical entity', making the tool's purpose clear. It distinguishes from siblings like search and entity_profile by focusing on disambiguation to a canonical entity.
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 use when disambiguating a name to a known entity via optional hints, but does not explicitly state when to use or avoid this tool compared to siblings like entity_profile or search. No when-not or alternative references.
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, the description carries full burden. It accurately discloses the return value ('pong' if alive) and implies a non-destructive, read-only operation. No side effects are mentioned, but the behavior is straightforward and transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no superfluous words. It front-loads the key purpose ('Health check.') and immediately follows with the expected output.
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?
Given the tool's simplicity, zero parameters, and presence of an output schema (which covers return values), the description is fully sufficient. No additional context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist; schema coverage is 100%. The description adds no additional parameter meaning, but this is appropriate as there are none to describe. Baseline scoring for zero parameters is satisfied.
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 identifies the tool as a health check that returns 'pong' if the server is alive. It uses a specific verb ('Health check') and resource (server status), and easily distinguishes from sibling tools like 'connections' or 'search'.
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 implicitly indicates use for verifying server liveness but does not explicitly state when to prefer ping over alternatives. Given the context of simple health checks, the purpose is clear, but no alternatives or exclusions are mentioned.
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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