NebulaGraph MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: execute_query for general queries, find_neighbors for vertex adjacency, find_path for pathfinding, get_space_schema for schema inspection, and list_spaces for space enumeration. The descriptions reinforce these distinct functions, making tool selection unambiguous.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern (e.g., execute_query, find_neighbors, list_spaces) with clear, descriptive verbs. There are no deviations in style or convention, making the naming predictable and easy to understand across the set.
Tool Count5/5
With 5 tools, this server is well-scoped for graph database operations, covering essential functions like querying, traversal, pathfinding, and schema management. Each tool earns its place without feeling excessive or insufficient for the domain.
Completeness4/5
The tool set provides strong coverage for core graph operations, including query execution, neighbor and path finding, and space/schema inspection. A minor gap exists in CRUD operations for vertices or edges (e.g., create, update, delete), but agents can likely work around this with queries.
Average 2.7/5 across 5 of 5 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
- Last stable release on March 17, 2025
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions executing a query and returning results but lacks details on permissions, rate limits, side effects, or error handling. This is inadequate for a mutation tool with zero annotation coverage.
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 brief and structured with sections for Args and Returns, making it easy to scan. However, it's under-specified rather than concise, as key details are missing, but the format is efficient.
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 annotations, no output schema, and low schema coverage, the description is incomplete. It fails to explain query types, space context, result format, or error scenarios, leaving significant gaps for a tool with 2 required parameters.
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 lists parameters 'query' and 'space' but provides minimal semantics beyond their names (e.g., no format, examples, or constraints). This adds little value over the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'Execute a query' which provides a basic verb+resource combination, but it's vague about what type of query (e.g., database, graph, search) and doesn't distinguish from siblings like 'find_neighbors' or 'get_space_schema'. It's not tautological but lacks specificity.
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 'find_neighbors' or 'list_spaces'. The description only lists arguments and returns, offering no context or exclusions for usage.
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 carries the full burden of behavioral disclosure. It mentions that the tool returns neighbors, but does not describe traits like whether it's read-only, if it has side effects, performance characteristics, error handling, or rate limits. For a query tool with zero annotation coverage, this is a significant gap, though it doesn't contradict any annotations.
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 structured with sections for 'Args' and 'Returns', which is helpful, but it includes redundant information (e.g., repeating 'The neighbors of the specified vertex' in the Returns section). It is front-loaded with the core purpose, but some sentences could be more efficient (e.g., the Returns section adds little beyond the initial statement). Overall, it's adequately concise but not optimally streamlined.
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 annotations, no output schema, and 0% schema description coverage, the description is incomplete. It covers the basic purpose and parameter meanings but lacks crucial context: it doesn't explain what a 'neighbor' entails (e.g., direct connections, types of relationships), the structure of the return value, error conditions, or how it integrates with sibling tools. For a graph query tool, this leaves significant gaps for an AI agent.
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%, so the schema provides no parameter descriptions. The description adds basic semantics: it explains that 'vertex' is the 'vertex ID to query', 'space' is 'The space to use', and 'depth' is 'The depth of the query, default is 1'. This compensates partially by clarifying what each parameter represents, but it lacks details like format, constraints, or examples (e.g., what a 'space' is or valid 'depth' ranges).
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's purpose: 'Find the neighbors of the specified vertex' with a specific verb ('Find') and resource ('neighbors of the specified vertex'). It distinguishes from siblings like 'find_path' (which finds paths) and 'execute_query' (which executes queries), though it doesn't explicitly mention these distinctions. The purpose is not tautological (it explains what 'find_neighbors' means) and is not misleading.
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?
The description provides no guidance on when to use this tool versus alternatives. It does not mention sibling tools like 'find_path' (for finding paths between vertices) or 'execute_query' (for general queries), nor does it specify contexts or exclusions. Usage is implied only by the tool's name and purpose, with no explicit instructions.
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 provided, the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't describe important behavioral traits: whether this is a read-only operation, computational complexity, timeout risks, authentication requirements, or rate limits. The description is minimal and lacks behavioral context beyond the basic function.
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 structured with clear sections (Args, Returns) but includes redundant information. The parameter listing repeats what's in the schema without adding value. 'Returns: The path results' is vague and doesn't earn its place. The core purpose statement is front-loaded but could be more efficient.
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 5-parameter tool with no annotations and no output schema, the description is incomplete. It doesn't explain what a 'path' consists of, what format the results take, error conditions, or performance characteristics. The agent lacks sufficient context to use this tool effectively beyond basic parameter passing.
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 lists all 5 parameters with brief labels, but with 0% schema description coverage, it doesn't fully compensate. It adds basic meaning (e.g., 'src' is 'source vertex ID') but lacks details on format, constraints, or examples. The schema provides titles and types, but the description adds minimal semantic value beyond what's already in the schema structure.
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's purpose: 'Find paths between two vertices' which is a specific verb+resource combination. It distinguishes itself from sibling tools like 'find_neighbors' (which likely finds adjacent vertices) and 'execute_query' (more general). However, it doesn't explicitly differentiate from siblings beyond the core function.
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?
The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites, when this tool is appropriate compared to 'find_neighbors' or 'execute_query', or any constraints on usage. The agent must infer usage from the tool name and parameters alone.
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 carries full burden. It mentions the tool returns 'The available spaces' but doesn't disclose behavioral traits like whether this is a read-only operation, if it requires authentication, how results are formatted (e.g., pagination, ordering), or potential rate limits. This leaves significant gaps for a tool with no annotation coverage.
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 appropriately sized with two short sentences, but it's not perfectly structured. The first sentence states the purpose clearly, but the second sentence ('Returns: The available spaces') is redundant and adds little value, slightly reducing efficiency. Overall, it's concise but could be more streamlined.
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's simplicity (0 parameters, no output schema), the description is incomplete. It lacks details on what 'spaces' are, how results are returned (e.g., list format, metadata), and behavioral context like safety or performance. Without annotations or output schema, the description should provide more context to be fully helpful.
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?
The tool has 0 parameters, and schema description coverage is 100%, so there's no need for parameter details in the description. The baseline for 0 parameters is 4, as the description appropriately doesn't discuss parameters that don't exist, and the schema fully covers the input structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool's purpose ('List all available spaces') which is clear but vague. It doesn't specify what 'spaces' are or how they differ from other resources, and doesn't distinguish this from sibling tools like 'get_space_schema' or 'find_neighbors'. The purpose is understandable but lacks specificity.
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. The description doesn't mention sibling tools like 'get_space_schema' for schema information or 'find_neighbors' for relationships, nor does it specify prerequisites or appropriate contexts for listing spaces versus other operations.
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 provided, the description carries the full burden of behavioral disclosure. It states this is a read operation ('Get'), but doesn't describe what 'schema information' includes, whether there are permissions required, rate limits, error conditions, or what format the return data takes. For a tool with zero annotation coverage, this is inadequate.
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 appropriately concise with three sentences that each serve a purpose: stating the tool's function, documenting the parameter, and describing the return. It's front-loaded with the core purpose first. The structure is clear but could be slightly more polished.
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 no annotations, no output schema, and minimal parameter documentation, the description is incomplete. It doesn't explain what 'schema information' means in this context, what format it returns, or any behavioral aspects. For a tool that presumably returns structured data about schemas, this leaves too much undefined.
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%, so the description must compensate. It documents the single parameter ('space') and explains it's 'The space to get the schema for', which adds semantic meaning beyond the schema's basic type information. However, it doesn't explain what constitutes a valid 'space' value or provide examples, leaving significant gaps.
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's purpose with a specific verb ('Get') and resource ('schema information of the specified space'). It distinguishes from siblings like 'list_spaces' (which lists spaces) and 'execute_query' (which runs queries). However, it doesn't explicitly differentiate from potential schema-related tools that might exist elsewhere.
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. The description doesn't mention prerequisites, when this tool is appropriate versus other schema discovery methods, or any constraints on its use. It simply states what the tool does without context.
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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