RabbitMQ MCP Server

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.0.0
Disambiguation5/5
Each tool targets a distinct resource and action: connect/status/disconnect manage connection, queue/exchange operations are separate, publish vs publish_to_queue are clearly differentiated by target (exchange vs default exchange), and get_message vs queue_message_count serve different purposes. No two tools appear to do the same thing.
Naming Consistency4/5
The naming follows a consistent rabbitmq_<verb>_<noun> pattern for most tools (e.g., list_queues, declare_queue, delete_queue). Minor deviations exist: 'rabbitmq_status' uses a noun instead of a verb phrase, and 'rabbitmq_queue_message_count' is an awkward noun-heavy construction rather than a verb-first name. Overall the pattern is predictable and readable.
Tool Count4/5
16 tools is slightly above the typical well-scoped range of 3-15, but the breadth is justified by covering connection management, queue and exchange lifecycle, bindings, publishing, and message retrieval. It does not feel bloated or redundant, given the full RabbitMQ management surface.
Completeness4/5
The tool surface covers core RabbitMQ operations: connection handling, queue/exchange CRUD, bindings, publishing, and message inspection. Minor gaps exist, such as no list_bindings or get_exchange tool, but agents can still perform most common workflows. No severe missing operations that would cause failures.
Average 3.3/5 across 16 of 16 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI 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.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It only states 'Declare a new exchange' and omits critical behavioral details such as idempotency (what happens if the exchange already exists), durability implications, or error behavior. This is severely under-transparent for a resource-creating operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence with no filler, but it is under-specified rather than appropriately concise, resembling the 'Process' example. It fails to include essential usage or behavioral context that a complete tool description should contain.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, and a single-sentence description, the tool lacks contextual completeness. It does not explain what 'declare' means in RabbitMQ, whether it is safe to call repeatedly, what properties are required, or what the result is. The rich sibling context and schema cannot compensate for the missing high-level guidance.
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 (durable, exchange_name, exchange_type) having a description and exchange_type listing an enum. The tool description adds no parameter-specific meaning, but the schema already provides sufficient semantics, warranting the baseline score of 3.
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 uses the specific verb 'declare' and identifies the resource as 'exchange', clearly indicating it creates/configures an exchange. While it doesn't explicitly contrast with sibling tools like rabbitmq_declare_queue, the resource name is sufficient to differentiate it.
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?
There is no guidance about when to use this tool versus alternatives such as rabbitmq_list_exchanges or rabbitmq_delete_exchange. The description provides no context about preconditions (e.g., needing an active connection) or scenarios for which this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as the destructive nature of the operation, potential impact on bindings, or the meaning of if_unused. The description simply restates the action without adding transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely brief, but it is under-specified rather than efficiently concise. It provides no information beyond the tool name, failing to earn its place as a useful description.
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 destructive operation with no annotations and no output schema, the description is inadequate. It omits context about connection requirements, side effects on bound queues, or the role of if_unused, leaving the agent without sufficient information to use the tool 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?
The input schema provides complete descriptions for both parameters (exchange_name and if_unused), so the description adds no additional semantic value beyond what is already in the schema.
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 'Delete an exchange' clearly states the specific verb (delete) and resource (exchange), which distinguishes it from sibling tools like rabbitmq_list_exchanges and rabbitmq_delete_queue.
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?
There is no guidance on when to use this tool over alternatives, no mention of prerequisites or related tools. The description provides no context for when deletion is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. It only restates the purpose and offers no additional context such as read-only nature, return format, error behavior, or whether it requires an active connection. This adds no transparency beyond the literal meaning.
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 concise sentence with no superfluous words. It is front-loaded and communicates the core function efficiently, appropriate for a simple read-only count operation.
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?
The tool has a minimal schema and no output schema. The description does not mention return type (e.g., integer), behavior when the queue does not exist, or any dependency on connection state. For a tool with no annotations, this is incomplete.
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% with queue_name described as 'Name of the queue'. The description does not add any additional meaning beyond the schema, which is the baseline expectation. For a single simple parameter, this is adequate.
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 'Get the number of messages in a queue' clearly states the action (get count) and the resource (a queue). It is specific and not a tautology, but it does not explicitly differentiate from sibling tools like rabbitmq_list_queues, which might also provide message counts.
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 such as rabbitmq_list_queues or rabbitmq_get_message. There is no mention of prerequisites (e.g., connection) or context that would help an agent choose this tool 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?
With no annotations present, the description carries the full burden of behavioral disclosure. It only states the action without describing return values, side effects, or failure modes (e.g., whether it throws if not connected). This lack of detail is a significant gap for a connection check, especially in a toolset that includes connect/disconnect operations.
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, concise sentence that serves its purpose without redundancy. It front-loads the action and resource, making it easy to parse. There is no wasted 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?
Although the tool has zero parameters and is simple, the description is incomplete because it doesn't specify the expected output or behavior when connected vs. disconnected. Since there is no output schema, the description should explain the return value, but it doesn't. This leaves the agent unclear about what to expect from the tool.
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 is empty, resulting in 100% schema description coverage. Baseline is 3 because the description doesn't need to explain parameters; there are none. The description adds no parameter-level detail, but none is required.
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 states a clear action ('Check connection status') and a specific resource ('RabbitMQ broker'). It distinguishes from sibling tools like rabbitmq_connect and rabbitmq_disconnect, though it leaves ambiguity about what 'status' entails (e.g., whether it's for the current session or the broker generally).
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. For instance, it doesn't mention that this should be used before publishing to verify connectivity, or that it's a read-only operation. The absence of any contextual cues leaves the agent to infer usage from the tool name 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?
With no annotations, the description carries the full burden of behavioral disclosure. It only adds that a quorum queue is created by default, which is already stated in the schema's default for queue_type. It fails to disclose idempotency (declare behavior if the queue exists), error cases, or that this is a mutating operation, which is critical for an agent to safely invoke.
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 two short sentences, front-loaded with the action and resource name. It avoids fluff and is immediately scannable, making it appropriately concise for the tool's simple purpose.
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 no annotations and no output schema, the description is insufficient for an agent to understand important context: what happens when a queue with the same name exists, whether rights/permissions are required, and whether the operation is safe or destructive. The schema provides parameter defaults but not behavioral context, leaving a significant gap in 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?
Schema description coverage is 100%, so the baseline is 3. The description adds no extra semantic detail beyond the schema's field descriptions. It only repeats the queue_type default, which is already present in the schema, providing no additional value for parameter understanding.
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 action ('Declare') and the resource ('a new queue'), which distinguishes it from sibling tools like rabbitmq_declare_exchange and rabbitmq_delete_queue. It also adds a specific default behavior ('Creates quorum queue by default'), making the purpose unambiguous.
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 given on when to use this tool vs alternatives, nor any exclusions or prerequisites. The description simply states what it does, leaving the agent to infer usage from the tool name. It does not differentiate from other queue-related tools (e.g., rabbitmq_delete_queue, rabbitmq_purge_queue).
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?
Since no annotations are provided, the description must disclose behavioral traits. It merely states the action without noting idempotency, side effects, or what happens if already disconnected.
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 concise sentence with no wasted words, appropriate for a simple operation.
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 trivial operation and empty schema, the description covers the core purpose but lacks context about connection lifecycle and interaction with other RabbitMQ tools.
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?
With zero parameters, the schema is empty and description correctly adds no parameter details, matching the baseline for no-param tools.
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 uses the specific verb 'Disconnect' and the target resource 'RabbitMQ broker', clearly distinguishing it from sibling tools like rabbitmq_connect and status. It lacks elaboration but is unambiguous.
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 given on when to use this tool, such as after rabbitmq_connect or for cleanup. It does not mention alternatives or exclusions, leaving the agent without 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, the description carries the full burden of behavioral disclosure. It does not mention that purging is destructive and irreversible, nor any side effects such as impact on consumers or message loss. The word 'Remove' is too mild for a purge operation.
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 that directly communicates the core operation with no filler words. It is appropriately sized for the simplicity of the tool.
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?
The description covers the basic action but lacks critical context for a destructive operation, such as noting that the action is irreversible, may affect consumers, or that there is no confirmation step. Given the tool's potential impact, the description is under-specified.
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 fully describes the only parameter (queue_name) with a clear description. Since schema coverage is 100%, the description does not need to add more, but it also does not provide any extra context beyond what the schema already offers.
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 action (Remove) and the resource (all messages from a queue), making it distinct from siblings like delete_queue (removes the queue itself) or publish (adds messages). It is specific and unambiguous.
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 simply states what it does without any use-case context, prerequisites, or exclusions.
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 only states the action and does not mention irreversibility, prerequisites (e.g., requiring an active connection), failure modes when the queue does not exist, or the effect on bound exchanges or consumers.
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 fluff. It states the core purpose directly and efficiently, earning its place without any 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?
Given the simplicity of the tool and high schema coverage, the description is minimally viable but lacks important context such as return behavior, error conditions, and any dependency on a prior connection (sibling rabbitmq_connect suggests this). The absence of an output schema and annotations increases the need for such context, which is not provided.
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 all parameters are already well-documented in the input schema. The tool description adds minimal semantic value beyond the schema; the only slight addition is the 'vhost' context, which is not needed for parameter interpretation.
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 'Delete a queue from the vhost' clearly states a specific verb and resource, making it easy to distinguish from sibling tools like rabbitmq_purge_queue (which only clears messages) and rabbitmq_delete_exchange (which targets a different resource type).
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 explicit guidance is provided about when to use this tool vs. alternatives such as purge_queue. The presence of if_empty and if_unused parameters hints at safe deletion conditions, but the description does not state when deletion is appropriate or how it differs from purging or 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, the description carries the full burden of behavioral disclosure, but it only states the basic action. It does not mention side effects (e.g., whether the exchange must already exist, whether message is fire-and-forget, or if publishing affects queues), leaving key behavioral traits undisclosed.
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 that immediately states the tool's action without unnecessary words. It is front-loaded and highly scannable, fitting the conciseness standard.
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?
For a simple publish operation with full schema coverage, the description is minimally viable. However, it lacks information about alternatives and behavioral expectations, which are relevant given the sibling tools. This leaves the agent with some uncertainty about proper 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?
The schema already provides 100% coverage with clear descriptions for all four parameters, so the description adds no additional parameter semantics. Baseline of 3 is appropriate since the schema handles parameter meaning effectively.
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 ('Publish') and specifies the resource ('exchange with a routing key'), which clearly distinguishes it from the sibling tool rabbitmq_publish_to_queue. It directly conveys the core function without ambiguity.
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 rabbitmq_publish_to_queue. It does not mention exclusions or preferred contexts, leaving the agent to infer usage purely from the tool name and siblings.
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 does not disclose important behavioral traits such as idempotency, whether the queue/exchange must already exist, or side effects like modifying existing bindings.
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 unnecessary words. It immediately conveys the core action and objects, earning its place efficiently.
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?
The description is minimal for a mutation tool with no annotations or output schema. It lacks context about prerequisites, failure modes, or return behavior, which are important for a complete understanding.
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% with clear descriptions for all three parameters. The description does not add extra meaning beyond the schema, but baseline 3 is appropriate given the schema handles the 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?
The description clearly states the action (bind), the objects involved (queue and exchange), and the routing key parameter. It effectively distinguishes from the sibling tool 'unbind_queue' by its opposite purpose.
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 the tool is used to establish a binding between a queue and an exchange, but it does not explicitly mention when to use it versus alternatives like unbind_queue. No exclusions or prerequisites are provided.
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 responsibility for behavioral disclosure. It only states the action and does not mention effects, errors, idempotency, or whether messages are affected, which is a notable gap for a mutation 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?
A single, front-loaded sentence conveys the tool's purpose with no wasted words or filler.
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 tool is simple and all parameters are well-documented, but with no output schema and no behavioral details, the description is only minimally complete. It adequately covers the core action but leaves edge cases and side effects unaddressed.
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 fully describes all three parameters with clear descriptions, so the description adds little beyond the action. Baseline 3 applies due to high 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 uses the specific verb 'Unbind' with clear resources (queue, exchange). It naturally distinguishes itself from the sibling tool rabbitmq_bind_queue.
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?
No explicit guidance is given about when to use this tool versus alternatives. However, the action's purpose implies it should be used to remove a binding between a queue and an exchange.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey behavioral traits. It discloses the use of the default exchange, but fails to mention prerequisites (e.g., existing connection/queue), delivery semantics (e.g., message dropped if queue absent), or side effects. This is minimal operational insight.
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 concise sentence that immediately states the action and scope. No filler or redundant content, fully front-loaded.
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 publish operation with no annotations or output schema, the description is insufficient. It omits critical context such as whether a connection must be established, whether the queue must exist, and what happens if the queue is not found. The agent lacks enough information for correct invocation in non-trivial scenarios.
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 (queue_name, message, content_type) already having a clear description. The tool description adds no additional meaning about parameters beyond what the schema provides, so the baseline of 3 applies.
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's function: 'Publish a message directly to a queue'. The phrase 'using default exchange' distinguishes it from sibling tools like rabbitmq_publish, which likely publishes via a specified exchange. The verb+resource+scope is specific and unambiguous.
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 gives clear context for when to use this tool: when you want to send a message directly to a queue via the default exchange. However, it does not explicitly name alternatives or state when not to use it, e.g., when routing via a custom exchange. This is clear context but lacks explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral transparency. It only states 'using Management API' and 'connected vhost', giving minimal context. It does not disclose that this is a read-only operation, what happens if no connection exists, or any error/return 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?
The description is a single, focused sentence that immediately states the action and target. It is concise without any wasteful words, earning full marks for structure.
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 is adequate for a simple list operation, but lacks explicit mention of what the return value is (e.g., exchange names/details) and does not explicitly state the dependency on an active connection. Since there is no output schema, more detail on return format would improve completeness.
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 zero parameters, so there is no schema to compensate for. The description correctly avoids adding unnecessary param details, and the baseline of 4 is appropriate given no parameters exist.
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 'List' with a clear resource 'exchanges' and scope 'in the connected vhost'. It clearly distinguishes this from sibling tools like list_queues by explicitly naming the resource type.
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 context by mentioning 'connected vhost', suggesting a prerequisite of an active connection. However, it does not explicitly state when to use this over alternatives or provide any exclusions, leaving usage guidance largely implicit.
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 carries the full burden. It discloses the connection context ('connected vhost') and method ('Management API'), but does not describe return format, side effects, or error behavior. For a simple read-only list operation, this is adequate but leaves gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence with no filler. Every word adds value: action, object, scope, and method.
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?
For a tool with no params, no annotations, and no output schema, the description gives the essential action but not the shape of the result (e.g., queue names vs. full attributes). It is sufficient for a basic list, but not fully complete given the presence of related tools that might imply different return data.
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?
There are zero parameters, so schema coverage is 100% by default. The baseline is 4, and the description adds no parameter information (none needed). This 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 action ('List'), the resource ('queues'), and the scope ('in the connected vhost'). It distinguishes from sibling tools like rabbitmq_list_exchanges by explicitly naming queues as the target.
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 implied usage is to enumerate queues, but there is no explicit guidance on when to prefer this over alternatives like rabbitmq_queue_message_count or rabbitmq_get_message. No exclusions or prerequisites are mentioned.
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 must disclose behavior itself, and it does: it explicitly states the non-destructive peek capability and that auto_ack removes the message. However, it omits details about empty-queue behavior, potential blocking, or connection prerequisites, which are relevant for a tool interacting with a queue.
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 that starts with the verb and objective, then adds the parenthetical nuance about modes. It conveys all necessary information without unnecessary words.
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?
There is no output schema and no annotations, so the description should explain what the tool returns (e.g., message content, null if empty) and any prerequisites like being connected. It also fails to mention the behavior when the queue is empty, which is an important omission for a 'get' 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?
The schema description already covers 100% of the parameters (queue_name and auto_ack) with clear meaning. The description adds minimal extra value, merely echoing the 'with ack' concept already captured in the schema's auto_ack field. Baseline 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 uses a specific verb 'Get' and resource 'a single message from a queue', immediately conveying the tool's core function. It also distinguishes two consumption modes (non-destructive peek vs. with ack), which sets it apart from sibling tools like publish or queue management.
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 clearly implies when to use this tool versus alternatives by outlining the two modes (peek vs. ack), but it does not explicitly name alternatives or exclusions. For example, it doesn't say 'use rabbitmq_queue_message_count if you only need a count,' though the context is still sufficiently clear.
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 discloses the required environment variables, which is useful configuration context. However, with no annotations, it fails to mention what happens upon successful connection, whether it is idempotent, or any error behavior, leaving the full behavioral burden on the description.
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 that efficiently lists the required environment variables. Every word contributes necessary information, with no waste.
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 connection tool with no parameters and no output schema, the description adequately covers the setup steps. It lacks details on return values or usage order relative to other tools, but the low complexity keeps this gap minor.
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?
With zero parameters, the schema provides no meaning. The description compensates by listing the environment variable configuration needed, which adds clarity beyond the empty schema.
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 the specific verb "Connect" with the resource "RabbitMQ broker", clearly distinguishing this from siblings that operate on queues/exchanges. It also specifies the mechanism (environment variables), making the purpose unambiguous.
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 clearly states that environment variables must be set before calling, implying a prerequisite for connection. However, it does not explicitly say when to use this tool relative to the sibling tools (e.g., as a prerequisite) or mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![rabbitmq_mcp MCP server](https://glama.ai/mcp/servers/sobue-code/rabbitmq_mcp/badges/card.svg)](https://glama.ai/mcp/servers/sobue-code/rabbitmq_mcp)

Score Badge

Copy to your README.md:

[![rabbitmq_mcp MCP server](https://glama.ai/mcp/servers/sobue-code/rabbitmq_mcp/badges/score.svg)](https://glama.ai/mcp/servers/sobue-code/rabbitmq_mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/sobue-code/rabbitmq_mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server