A
licenseNot graded
qualityF
maintenanceA Model Context Protocol (MCP) server that enables LLMs to interact directly with MongoDB databases. Query collections, inspect schemas, and manage data seamlessly through natural language.
47
175
MIT
MongoDB
by kiliczsh
The MCP MongoDB Server enables interaction with MongoDB databases through a standardized interface, allowing both read and write operations.
Read Operations: Query documents, execute aggregation pipelines, count documents, and get collection schema information.
Write Operations: Update documents, insert new documents, and create indexes (when not in read-only mode).
Smart ObjectId Handling: Convert between string IDs and MongoDB ObjectId with configurable modes.
Read-Only Mode: Protect against write operations in production environments.
Server Information: Retrieve MongoDB server details, including version and storage engine.
Collection Management: List available collections and inspect their schemas.
LLM Integration: Enhanced interaction with collection completions and schema inference.
Flexible Configuration: Set connection parameters via environment variables or command-line options.
Provides access to MongoDB databases, allowing LLMs to inspect collection schemas and execute MongoDB operations like queries, aggregations, updates, inserts, and creating indexes
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MongoDBshow me the schema for the users collection"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP MongoDB Server
A Model Context Protocol (MCP) server that lets AI assistants work with your MongoDB databases. It exposes your collections, infers their schemas, and runs queries, aggregations, and writes through a standard interface — so tools like Claude Desktop and Cursor can read and reason about your data.
Demo
Related MCP server: MongoDB MCP Server for LLMs
Why use it
Talk to your database in plain language — the assistant discovers your collections and their shape automatically.
Safe by default — turn on read-only mode to let an assistant explore without any risk of changing data.
Works everywhere — connects to standalone, replica set, sharded, and Atlas deployments, over plain or TLS connections.
Key Features
Read-Only Mode — blocks every write path (insert, update, index creation, and aggregation stages like
$out/$mergethat could modify data).Smart ObjectId Handling — configurable
auto/none/forceconversion of 24-character hex strings to ObjectIds.Schema Inference — automatic collection schema detection from document samples.
Query & Aggregation — full query and aggregation pipeline support, with optional
explainplans.Write Operations — insert, update, and index creation (when read-only mode is off).
Time Conversion — a
convertTimehelper turns Unix timestamps and date strings into UTC/GMT/ISO, so date queries stay unambiguous across timezones.Progress & Cancellation — long operations report progress and can be cancelled mid-flight.
Two Transports — run locally over stdio, or expose an HTTP endpoint for remote access.
Requirements
Node.js 20 or newer
Quick Start
Point the server at your database — no install step needed:
npx -y mcp-mongo-server mongodb://localhost:27017/mydatabaseExplore safely, without any chance of changing data:
npx -y mcp-mongo-server mongodb://localhost:27017/mydatabase --read-onlyUsage
Local (stdio)
This is the default, used by Claude Desktop, Cursor, and other local clients:
npx -y mcp-mongo-server "mongodb://user:pass@localhost:27017/mydatabase"Remote (HTTP)
Expose an HTTP endpoint at /mcp for remote or multi-client access:
npx -y mcp-mongo-server "mongodb://user:pass@localhost:27017/mydatabase" --transport http --port 3001By default, only requests without a browser Origin (CLIs, IDEs) and requests
from localhost are accepted; everything else is rejected with 403 to guard
against DNS-rebinding attacks. Allow specific browser origins with
--allowed-origins:
npx -y mcp-mongo-server "mongodb://..." --transport http --port 3001 --allowed-origins "https://app.example.com"Options
Flag | Description |
| Block all write operations |
| Allow aggregation |
| Allow server-side JavaScript operators |
|
|
| HTTP port (default |
| Comma-separated browser origins to allow in HTTP mode |
| Max HTTP request body size (default |
| Require |
Environment Variables
Variable | Description |
| MongoDB connection URI (alternative to the argument) |
| Enable read-only mode ( |
| Allow cross-database aggregation stages ( |
| Allow server-side JavaScript operators ( |
| HTTP port |
| Comma-separated browser origins to allow in HTTP mode |
| Max HTTP request body size (default |
| Bearer token required to access the HTTP endpoint |
Security
Database scope. The server operates on the database in your connection
string. Aggregation stages that reach another database ($out, $merge,
$lookup with an explicit db) are rejected by default, so a pipeline can't
quietly read from or write to databases you didn't point it at. Enable them
with --allow-cross-db if you need them.
Server-side JavaScript. The aggregation operators $function, $where,
and $accumulator run arbitrary JavaScript on the MongoDB server. They are
rejected by default; enable them with --allow-server-js if you trust the
pipelines being run.
Read-only mode blocks every write path, including aggregation stages that
write or run server-side JavaScript ($out, $merge, $function, $where,
$accumulator).
Least privilege. Application-level checks only go so far — the strongest guarantee comes from the database. Connect with a MongoDB user scoped to just the database you need, with read-only permissions when the assistant only needs to explore. That way the database itself enforces the boundary, as defense in depth.
Documentation
Integration Guide — Claude Desktop, Windsurf, Cursor, Docker
Available Tools — query, aggregate, update, insert, and more
Development — setup, scripts, and debugging
License
MIT — see LICENSE for details.
Available Tools
8 toolsaggregateB
Execute a MongoDB aggregation pipeline with optional execution plan analysis
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| explain | No | Optional: Get aggregation execution information (queryPlanner, executionStats, or allPlansExecution) | |
| pipeline | Yes | Aggregation pipeline stages | |
| collection | Yes | Name of the collection to aggregate | |
| objectIdMode | No | Control how 24-character hex strings are handled | auto |
TDQS
B3.2/5.0
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.
Conciseness5/5
Is 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.
Completeness2/5
Given 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.
Parameters3/5
Does 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.
Purpose5/5
Does 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 Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives 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.
countC
Count documents in a collection matching a query
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| hint | No | Index hint | |
| skip | No | Docs to skip before counting | |
| limit | No | Max documents to count | |
| query | No | Query filter to count | |
| collation | No | Collation rules for comparison | |
| maxTimeMS | No | Max execution time | |
| collection | Yes | Collection name | |
| readConcern | No | Read concern option | |
| objectIdMode | No | Control how 24-character hex strings are handled | auto |
TDQS
C2.9/5.0
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.
Conciseness4/5
Is 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.
Completeness2/5
Given 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.
Parameters3/5
Does 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.
Purpose4/5
Does 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 Guidelines2/5
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 (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.
createIndexB
Create one or more indexes on a MongoDB collection
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| indexes | Yes | Array of index specifications | |
| collection | Yes | Name of the collection to create indexes on | |
| commitQuorum | No | Number of members required to create the index | |
| objectIdMode | No | Control how 24-character hex strings are handled | auto |
| writeConcern | No | Write concern for index creation |
TDQS
B3.1/5.0
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.
Conciseness4/5
Is 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.
Completeness2/5
Given 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.
Parameters3/5
Does 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.
Purpose5/5
Does 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 Guidelines2/5
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, 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.
insertB
Insert one or more documents into a MongoDB collection
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| ordered | No | If true, perform ordered insert. If false, insert unordered | |
| documents | Yes | Array of documents to insert | |
| collection | Yes | Name of the collection to insert into | |
| objectIdMode | No | Control how 24-character hex strings are handled | auto |
| writeConcern | No | Write concern for the insert operation | |
| bypassDocumentValidation | No | Allow insert to bypass schema validation |
TDQS
B3.1/5.0
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.
Conciseness4/5
Is 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.
Completeness2/5
Given 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.
Parameters3/5
Does 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.
Purpose5/5
Does 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 Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (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.
listCollectionsB
List all collections in the MongoDB database
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| filter | No | Filter for collections | |
| nameOnly | No | If true, return only collection names | |
| objectIdMode | No | Control how 24-character hex strings are handled | auto |
TDQS
B3.1/5.0
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.
Conciseness4/5
Is 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.
Completeness2/5
Given 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.
Parameters3/5
Does 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.
Purpose5/5
Does 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 Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. 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.
queryB
Execute a MongoDB query with optional execution plan analysis
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of documents to return | |
| filter | No | MongoDB query filter | |
| explain | No | Optional: Get query execution information | |
| collection | Yes | Name of the collection to query | |
| projection | No | Fields to include/exclude | |
| objectIdMode | No | Control how 24-character hex strings are handled | auto |
TDQS
B3.2/5.0
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.
Conciseness5/5
Is 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.
Completeness2/5
Given 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.
Parameters3/5
Does 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.
Purpose5/5
Does 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 Guidelines2/5
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 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.
serverInfoA
Get MongoDB server information including version, storage engine, and other details
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| includeDebugInfo | No | Include additional debug information about the server |
TDQS
A3.7/5.0
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.
Conciseness4/5
Is 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.
Completeness4/5
Given 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.
Parameters3/5
Does 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.
Purpose5/5
Does 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 Guidelines3/5
Does 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.
updateC
Update documents in a MongoDB collection
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| multi | No | Update multiple documents that match the filter | |
| filter | Yes | Filter to select documents to update | |
| update | Yes | Update operations to apply ($set, $unset, $inc, etc.) | |
| upsert | No | Create a new document if no documents match the filter | |
| collection | Yes | Name of the collection to update | |
| objectIdMode | No | Control how 24-character hex strings are handled | auto |
TDQS
C2.8/5.0
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.
Conciseness3/5
Is 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.
Completeness2/5
Given 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.
Parameters3/5
Does 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.
Purpose4/5
Does 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 Guidelines2/5
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 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.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
8 tool updates
v1.0.0- First observed
aggregate - First observed
count - First observed
createIndex - First observed
insert - First observed
listCollections - First observed
query - First observed
serverInfo - First observed
update
TDQS
B3.4/5.0
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 Consistency5/5
All 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 Count5/5
8 tools cover core MongoDB operations (CRUD, aggregation, indexing, metadata) without being too few or excessive for a general-purpose database server.
Completeness2/5
The 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.
Maintenance
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- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
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