MongoDB
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool targets a distinct database operation: aggregation, counting, indexing, inserting, listing collections, querying, server info, and updating. No two tools have overlapping purposes.
Naming Consistency5/5All tool names use lowercase with camelCase for multi-word terms (e.g., 'createIndex', 'listCollections', 'serverInfo'), following a consistent pattern of verb or verb_noun.
Tool Count5/58 tools cover core MongoDB operations (CRUD, aggregation, indexing, metadata) without being too few or excessive for a general-purpose database server.
Completeness2/5The set lacks a tool for deleting documents or collections, which is a fundamental operation. Without 'delete' or 'remove', agents cannot complete typical data lifecycle actions, leaving a significant gap.
Average 3.1/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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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, the description solely must clarify behavior. It only states the operation type (update) but omits details like whether the tool returns the updated document, handles no-matches, or requires authentication. The rich schema parameters (multi, upsert) are not elaborated beyond their definitions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but at the cost of informative detail. It does not front-load key behavioral cues (e.g., upsert support) and is thus minimal rather than optimally structured.
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?
For a tool with 6 parameters, nested objects, and no output schema, the description lacks completeness. It does not explain return values, error scenarios, or behavior of multi/upsert combinations, leaving significant gaps for an agent to use correctly.
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 coverage is 100%, so each parameter has a description. The tool description adds no extra parameter context, meeting the baseline for high coverage. However, no additional semantic elaboration is provided for complex parameters like 'update' (MongoDB operators) or 'objectIdMode'.
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 tool updates documents in a MongoDB collection using a clear verb-resource structure. However, it does not distinguish this tool from siblings like 'insert' (creates) or 'query' (reads), leaving some ambiguity about the specific operation scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 such as 'insert' for new documents or 'aggregate' for transformations. There is no mention of prerequisites, idempotency, or context-specific conditions.
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 full burden for behavioral disclosure. It only states the basic operation without detailing any side effects (none expected for a count), return format, or constraints (e.g., counting behavior with skip/limit). The agent cannot infer that this is a read-only operation or what the output structure is.
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, efficient sentence that directly states the core function. However, it is overly terse and lacks structured details that would aid the agent, such as separating purpose from usage notes. Score reflects conciseness but slight under-information.
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 9 parameters, no output schema, and no annotations, the description is insufficiently complete. It omits essential information like the return type (a count number), whether the count is approximate or exact, and behavior with optional parameters like skip/limit. A more complete description would provide contextual completeness.
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 100% coverage with descriptions for all 9 parameters. The description adds no additional parameter semantics beyond what is already in the schema. Per guidelines, baseline is 3 when schema coverage is high, and no extra value is provided.
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 'count' and the resource 'documents in a collection matching a query', which accurately defines the tool's purpose. However, it does not explicitly distinguish this tool from sibling tools like 'aggregate' or 'query', which could also perform counting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 (e.g., 'aggregate' for more complex aggregations). There are no examples, prerequisites, or exclusions mentioned, leaving the agent without sufficient context to choose appropriately.
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 carry the burden of behavioral disclosure. It only states the action without mentioning side effects like blocking operations, performance implications, or permission requirements. This is inadequate for a mutation tool that can significantly affect database behavior.
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 concise sentence that is front-loaded with the core action. However, it is extremely brief given the tool's complexity. It earns its place but could benefit from a bit more structure.
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 including nested objects and no output schema, the description is insufficient. It does not explain that multiple indexes can be created, the return behavior, or important aspects like background building. The agent lacks key information 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?
Schema description coverage is 100% with each parameter having a description. The tool description adds no additional semantics beyond the schema. Baseline of 3 is appropriate as the schema does the heavy lifting.
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 purpose: creating one or more indexes on a MongoDB collection. The verb 'create' and resource 'indexes on a MongoDB collection' are specific, and the tool is distinct from siblings like 'aggregate' or 'insert' that do not create indexes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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, or prerequisites for index creation. The description lacks context about when indexes should be created or potential impacts, leaving the agent without decision support.
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 description must disclose behavior. It lacks details on handling duplicate _id errors, return values, or performance implications. Only states basic insert action.
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?
One short sentence with no waste, but could be more informative without being verbose. Front-loads the core action.
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 6 parameters including nested objects and no output schema, the description is insufficient. It should mention error handling, return format, and parameter default behaviors.
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 coverage is 100%, so baseline is 3. Description adds no extra meaning beyond the schema; it doesn't explain parameters like ordered, objectIdMode, or writeConcern.
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 'Insert' and the resource 'MongoDB collection', with 'one or more documents' specifying scope. It distinguishes from siblings like query (read) and update (modify) with a specific insert action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 (e.g., update for modifying, query for reading). No prerequisites or context about required permissions or collection existence.
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 carries full burden. It describes 'list' implying read-only, but fails to disclose behavior like pagination, authentication requirements, or how parameters like 'objectIdMode' affect execution.
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?
A single concise sentence that gets to the point. However, it could front-load more critical information like the database context, but for a simple tool it is appropriately sized.
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?
No output schema exists, and the description does not explain return values (e.g., list of names vs full documents). The 'nameOnly' parameter hints at different outputs, but this is not clarified. For a list tool with multiple parameters, more detail is needed.
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 100%, so baseline is 3. The description adds no extra meaning beyond the schema; it simply restates the tool's purpose without detailing parameter usage or constraints.
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 specific verb 'List' and resource 'collections in the MongoDB database', which distinguishes it from sibling tools like 'aggregate' or 'insert' that perform different operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. It does not mention contexts where other tools like 'query' might be more appropriate, nor any conditions for using this tool.
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 description carries full burden. It does not disclose whether the tool is read-only, can write via stages like $merge, or any potential side effects, performance implications, or required permissions.
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?
Single sentence of 12 words directly states the core functionality. No extraneous information, efficiently front-loads the action and optional feature.
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?
Despite being a complex tool (aggregation pipeline), the description lacks details on output format, error handling, potential performance costs, or the impact of the objectIdMode parameter. No output schema compounds the incompleteness.
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?
All four parameters are fully described in the input schema (100% coverage). The description adds minimal extra context, only mentioning 'optional execution plan analysis' which maps to the explain parameter. No further clarification on pipeline construction or objectIdMode behavior.
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?
Description clearly states the tool executes a MongoDB aggregation pipeline with optional execution plan analysis. It uses specific verb 'execute' and resource 'aggregation pipeline', distinguishing it from sibling tools like query, count, or insert.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 such as 'query' or 'count'. The description does not mention scenarios or limitations, leaving the agent to infer usage context.
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 must disclose behaviors. It only states execution of a query, but does not specify if this is read-only, side effects, permission needs, or performance implications.
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?
Single sentence that is direct and front-loaded with the core action. No unnecessary words, and the optional analysis is mentioned immediately.
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?
Despite having 6 parameters and no output schema, the description does not explain return values, pagination, or behavior for required parameters. It is too minimal for a complex MongoDB query operation.
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 100%, so each parameter is already documented. The description adds minor value by linking 'execution plan analysis' to the explain parameter, but does not provide additional semantic context.
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 executes a MongoDB query with optional execution plan analysis. The verb 'Execute' and resource 'MongoDB query' are specific, and the mention of execution plan analysis distinguishes it from basic query tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus siblings like aggregate or count. The description does not mention appropriate scenarios, prerequisites, 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 exist, so the description carries full burden. It correctly implies a read-only, non-destructive operation but does not disclose any specific behavioral traits such as authentication needs or rate limits. The effect of the optional parameter is not elaborated beyond the schema.
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, efficient sentence that conveys the core purpose. It is front-loaded and concise, though it could be slightly more structured.
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?
For a simple info tool with one optional parameter and no output schema, the description is mostly complete, stating the type of information returned. It lacks details about return format or explicit read-only guarantee, but is still adequate.
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 coverage is 100% and the parameter already has a description. The tool description adds no additional meaning about the parameter beyond what the schema provides, so a baseline score of 3 is appropriate.
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 gets MongoDB server information and lists examples like version and storage engine, distinguishing it from sibling tools that perform data operations (query, insert, etc.).
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 gives a clear purpose but does not explicitly state when or when not to use this tool versus alternatives. Context from sibling tools suggests usage, but no direct guidance is provided.
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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