bruno-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation4/5
Most tools have clearly distinct purposes: collections, requests, environments, and execution are cleanly separated. The only minor overlap is bruno_list_requests vs bruno_search_requests, but their scoping within a single collection vs across all collections is sufficiently differentiated.
Naming Consistency5/5All tool names follow the same bruno_<verb>_<noun> pattern with consistent verbs: list, get, run, and search. This makes the tool surface predictable and easy for an agent to navigate.
Tool Count5/5Seven tools is a well-scoped size for a Bruno-focused MCP server. Each tool covers a necessary operation for browsing and executing collections without unnecessary bloat.
Completeness4/5The set covers the core lifecycle for the apparent purpose of inspecting and running Bruno collections: list collections, list/search requests, read request details, inspect environments, and execute. It lacks create/update/delete operations, which may be intentional for a read/run-oriented server, but would be needed for full authoring workflows.
Average 3.9/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 33 commits in the last 12 weeks
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
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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
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the behavioral burden. It does add a useful, non-obvious behavior: 'Variables marked as secrets are always redacted.' However, it does not disclose other important traits such as read-only/no-side-effect behavior, not-found/error responses, or whether the full variable list is returned.
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?
The description is two sentences with no wasted words. The first sentence states the action and target, and the second adds an important caveat about secrets. It is front-loaded and easy to scan.
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 tool with two well-documented parameters and no nested schema, the description plus schema is sufficient for correct invocation. The redaction behavior is a key context detail. The main gaps are unspecified return format and failure behavior, but the low complexity makes those minor.
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 already covers both parameters at 100%, including detailed explanations of collection path conventions and environment reference forms. The description adds no additional parameter-level meaning, so the baseline score of 3 is appropriate.
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 uses a specific verb and resource: 'Inspect a Bruno environment.' It clearly identifies a single-environment inspection action, and the redaction note implies the output contains variables. It doesn't explicitly contrast itself with sibling tools like bruno_list_environments, but the singular 'environment' and title make the purpose reasonably clear.
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?
Usage context is only implied: an agent would infer this is for inspecting one Bruno environment rather than listing all environments. There is no explicit statement of when to use this vs. alternatives such as bruno_list_environments or when not to use it, so the guidance is adequate but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full transparency burden. It handles this well for a read-only list tool by explicitly stating that it returns request paths, names, types, and HTTP metadata when available, and by avoiding destructive or write semantics. Minor operational details like pagination or empty-result behavior are not disclosed, but the core behavior is clear.
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?
The description is two concise sentences with no filler. The primary action and resource are front-loaded, followed immediately by the key return information, so an agent can quickly determine what the tool offers.
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?
Given the rich schema and the absence of an output schema, the description usefully states the kind of data returned. It is sufficiently complete for a list-style tool, though it could be stronger with an explicit contrast to bruno_search_requests.
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 the input schema already documents all four parameters clearly, including collection path semantics and filter behavior. The tool description itself does not add parameter-level meaning beyond this, matching the baseline for high schema coverage.
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 states a clear verb ('List and search') and resource ('requests in a Bruno OpenCollection collection'), and it specifies the returned data (paths, names, types, HTTP metadata). However, it does not differentiate this tool from the sibling bruno_search_requests, whose purpose likely overlaps.
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 gives no guidance on when to use this tool versus alternatives such as bruno_search_requests or bruno_get_request. It also fails to clarify whether this tool's search behavior is a substitute for the dedicated search sibling or only a lightweight filter.
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 provided, the description carries the burden of behavioral disclosure. It clearly indicates this is a read operation that returns parsed YAML, and the includeSource parameter (described in the schema) adds transparency about optional raw-source output. It does not mention error behavior or permissions, but the read-only nature is explicit.
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?
The description is a single efficient sentence that states the core action and result without repetition or filler. It earns its place and is easy for an agent to parse quickly.
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 read tool with fully documented parameters, the description plus schema provides enough information for correct invocation. A brief note about when to prefer this over bruno_run or bruno_search_requests would make it complete, but nothing essential is missing for basic 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%, so the input schema fully documents all three parameters. The main description adds no parameter-level meaning beyond 'parsed YAML representation,' but the high schema coverage means the description does not need to compensate.
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 identifies a specific verb ('Read') and resource ('a Bruno OpenCollection request') and states the output format ('parsed YAML representation'). This distinguishes it from sibling list/search/run tools, making its purpose immediately clear.
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 itself does not explicitly state when to use this tool versus alternatives like bruno_run or bruno_search_requests. However, the parameter descriptions do provide useful context by explaining how to obtain valid collection and request identifiers from the sibling listing tools, so usage is implied rather than fully spelled out.
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 behavioral burden. 'List' implies a read-only operation and 'available in the configured workspace' adds scope context, but the description does not disclose output format, pagination, ordering, or error behavior. It is minimally adequate for a simple list operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that states the action, resource, and scope with no filler or redundant explanation. It is well-sized and immediately understandable.
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 zero-parameter, read-only list tool with no output schema, the description is largely sufficient: it names the action, resource, and scope. It could mention what information is returned or how the workspace is determined, but these are minor gaps for this complexity level.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameters, so there is no parameter documentation burden. The description adds workspace context but no parameter semantics are needed. Baseline 4 is appropriate for a zero-parameter tool.
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 uses a specific verb ('List') and a precise resource ('Bruno OpenCollection collections') and scopes it to the configured workspace. It is clearly distinguishable from the sibling tools, which target requests and environments rather than collections.
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 intended use is implied by the verb 'List' and the collection resource, but the description does not explicitly state when to choose this tool over siblings or mention any exclusions. It provides context (configured workspace) but no direct routing guidance.
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 provided, the description carries the behavioral disclosure burden. It usefully states that variable values will not be exposed, which is a meaningful guarantee. However, it says nothing about output shape, error behavior, or ordering, so transparency is adequate but not thorough.
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?
The description is a single well-structured sentence that front-loads the action and resource, then adds the important caveat about not exposing variable values. Every word earns its place.
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 one-parameter list tool with no output schema, the description covers the essential context: scope is the collection and variable values are intentionally withheld. It is slightly light on return-value expectations, but 'List environments' reasonably implies the returned artifact.
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 description already explains that 'collection' is a path relative to the workspace root with a nested example. The tool description reinforces the collection-scoped nature but does not add significant parameter semantics beyond the schema.
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 uses a specific verb and resource ('List environments available to a Bruno collection') and adds a distinguishing safety scope: 'without exposing variable values.' This clearly separates it from bruno_get_environment, which presumably returns variable values.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description conveys when to use the tool: to enumerate environments for a collection while deliberately avoiding variable value exposure. It does not explicitly name a sibling alternative, but the caveat makes the intended use case clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It discloses the scope ('all collections'), the execution model ('in a single call'), and the result shape ('each matching request tagged with its collection id'). It lacks explicit statements about pagination or error behavior, so it is not a 5, but it is transparent about the core behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no filler. The core behavior and scope are front-loaded, and the result behavior is stated succinctly. Every clause contributes value.
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 relatively simple search tool, the description plus schema covers scope, matching behavior, filters, and result tagging well. The lack of an output schema keeps it from a 5, since the exact structure of 'tagged' results is not fully specified.
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 provides 100% coverage for all three parameters, including semantics for query, type, and method. The description adds no parameter-level detail beyond what the schema already provides, so the baseline 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 states a specific action ('Search requests'), a clear resource scope ('across all Bruno OpenCollection collections in the workspace'), and highlights the 'single call' nature. The mention that results are tagged with collection id further distinguishes this from collection-scoped siblings like bruno_list_requests and bruno_get_request.
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 implies this tool is for cross-collection searching rather than per-collection listing or fetching, but it never explicitly names alternatives or states when not to use it. The usage context is clear enough, but there is no direct routing to sibling tools.
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 provided, the description carries the full transparency burden. It does well by disclosing that execution returns structured request/response/test/assertion results, that variable overrides must not contain secrets, and that MCP tool arguments may be visible to the model and host. This goes beyond the schema by explaining why secrets must be excluded.
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 appropriately front-loaded with purpose and return-value information, then turns to security guidance. It is slightly repetitive around secrets ('must not contain secrets' and 'do not pass credentials or other secrets'), but every sentence contributes useful information and the overall length is reasonable for a tool with 11 parameters and no annotations.
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 an 11-parameter execution tool with no output schema, the description is largely complete: it states what is executed, what results are returned, and critical security constraints. The schema covers parameter semantics and policy-gated flags, while the description adds the secret-handling context. Minor missing guidance around explicit sibling routing prevents a 5.
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 the schema already documents all 11 parameters. The description does not add new parameter-level meaning beyond repeating the variables security warning, which is already present in the schema's variable parameter description.
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 opens with a specific verb, 'Execute,' and names the exact resources: 'requests, folders, or an entire Bruno collection.' It also states the underlying implementation ('Bruno CLI v4') and describes the outcome, which clearly distinguishes this executor tool from the sibling list/get/search tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
While there is no explicit 'use this instead of X' statement, the description makes the tool's role unmistakable: it is the execution tool, contrasting with siblings that only list, get, or search. The scope ('requests, folders, or an entire collection') plus return-value description gives clear context for when an agent should invoke it.
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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