Mockzilla

Official

by mockzilla

Overview Schema Related Servers Score Discussions

JavaScript

Hybrid

Server Quality Checklist

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

Latest release: v0.1.0
Disambiguation5/5
Each tool has a well-defined, distinct purpose. No two tools appear to do the same thing; even closely related tools like mock_endpoint and serve_locally are clearly differentiated by scope and usage.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern (e.g., call_endpoint, install_cli, serve_locally). The naming is predictable and readable, with no mix of conventions.
Tool Count5/5
With 14 tools, the server is well-scoped. Each tool covers a necessary functionality for managing mocking workflows without being overwhelming or sparse.
Completeness4/5
The tool set covers installation, local serving, quick mocks, spec handling, and documentation access. A minor gap is the lack of a tool to delete a single mock endpoint, but the overall surface is comprehensive.
Average 4.6/5 across 14 of 14 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on May 2, 2026
- 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.
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.
This repository includes a glama.json configuration file.
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

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description explains the tool's non-destructive scanning behavior and output format. Reveals it returns a suggested_input for serve_locally, which is helpful. Could add depth limit or side effects, but adequate.
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?
Two sentences, no fluff, efficient word choice. First sentence states action and output, second gives usage context.
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?
Simple single-parameter tool with clear purpose. Description covers input, scan behavior, and output. Lacks output schema but hints at return value. Complete enough for this complexity.
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?
Only one parameter 'dir' with 0% schema coverage. Description implies it is a directory path but does not describe its format or constraints. Baseline 3 for single required parameter with implicit meaning.
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 scans a directory and reports OpenAPI spec files and static subdirs, with specific details like returning a suggested_input for serve_locally. This distinguishes it from siblings like peek_openapi.
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?
Explicitly provides user utterances that trigger this tool ('I have a folder of specs/files, what's in it?' or 'mock this directory'), giving clear context. Lacks explicit when-not-to-use or alternatives, but sufficient.
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?
No annotations are provided, so the description carries full burden. It transparently describes the output format (topic, heading, snippet) and implies read-only behavior via 'search' and 'identify which topic to read'. However, it does not explicitly state it has no side effects or require authentication, which is acceptable for a search 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?
Two sentences, zero waste. First sentence states action and result format. Second sentence provides usage guidance. Perfectly front-loaded.
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?
Given the tool has no output schema, the description adequately explains what is returned (topic, heading, snippet). It also provides usage context (use before answering). Could mention that limit controls the number of results, but that is partly in the schema. Overall complete for a search 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?
Schema description coverage is 50%: query is described well in the schema ('Free-text query...'), but limit lacks a description. The tool description adds no additional parameter context beyond the schema. The limit parameter is somewhat self-explanatory with min/max/default, but the description could have clarified its role (e.g., 'number of top results to return').
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 it searches docs by keyword and returns top-scoring sections with topic, heading, snippet. It distinguishes from siblings like mockzilla_docs_read (which reads full topics) and mockzilla_docs_topics (which lists topics) by focusing on search. The verb 'search' and resource 'mockzilla docs' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises to use this tool BEFORE answering questions about mockzilla syntax, conventions, or features when uncertain, stating 'the docs are the source of truth, your training is not'. This provides clear context for when to use vs. relying on memory, though it does not explicitly mention alternatives.
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?
Discloses search paths and response content (install_options), though does not detail whether it executes the CLI or just checks files.
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?
Concise and structured, though slightly verbose with user guidance that could be secondary.
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?
Covers key aspects: inputs (none), actions, and follow-up steps. No output schema, but description implies response structure.
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?
No parameters; baseline 4 applies. Description adds no parameter info but none is needed.
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 checks CLI availability across three specific locations, and distinguishes its use case as the first step for local mockzilla attempts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Call FIRST' and provides follow-up action: if unavailable, suggest install_cli with method options.
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 fully discloses installation methods, cache location, system PATH impact, and uninstall procedure. It is transparent about where files land and how to clean up, though could mention potential network usage or error scenarios.
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 concise (4 sentences) and front-loads the purpose and a key instruction. It could be improved with bullet points for the methods, but remains clear and avoids redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter, no output schema), the description is complete: it explains each method, side effects (cache location, not on PATH), and how to uninstall. No critical gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds substantial meaning beyond the schema: it explains each enum value (download: prebuilt binary, go-install: compile from source, go-run: use go run without install), including size, speed, and dependencies. This is essential given 0% schema description 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 clearly states 'Install the mockzilla CLI for this user' and details three specific methods, distinguishing the tool from siblings like check_cli and serve_locally.
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 instructs the agent to ask the user which method to use and lists prerequisites for each method (e.g., Go needed for go-install/go-run). It does not explicitly exclude scenarios but provides sufficient context for decision-making.
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?
Describes the return format and UI behavior when server is running; despite no annotations, it sufficiently discloses read-only behavior and UI side effect.
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 with return format and usage suggestion; no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Fully covers the tool's purpose, return structure, and contextual usage advice despite lacking an output schema.
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?
Zero parameters, baseline 4; no additional parameter info needed.
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?
Clearly states it lists all endpoints mocked via `mock_endpoint`, distinguishing it from sibling tools like `mock_endpoint` (create) and `clear_mock_endpoints` (delete).
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?
Provides explicit guidance to suggest the UI when the user wants to explore beyond chat, implying this tool is for basic listing while the UI offers richer interaction.
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?
No annotations provided, but description accurately describes read-only behavior. Could explicitly state it is a safe 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?
Two sentences, first states purpose, second gives usage guidance. No redundancy, front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, description is fully sufficient, explaining purpose, usage, and relation to sibling.
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 schema description already explains source and format. Description adds no extra meaning beyond tool 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?
Clearly states it returns full markdown for one doc topic, distinguishes from sibling `mockzilla_docs_search` by specifying when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use for deep, specific questions and to use `mockzilla_docs_search` for broader or unknown topics, providing clear context.
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?
Returns specific fields and is read-only. No annotations, but the description explains output and usage. Could mention external call but not required.
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?
Two sentences, efficient: first states purpose and output, second gives usage guidance. No redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complete for a simple status tool: describes action, return fields, and when to use. No output schema but description covers it.
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?
No parameters; schema coverage 100%. Description adds meaning by specifying return fields and usage, meeting baseline for 0 parameters.
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?
Clearly states it reports bridge version and checks for updates on npm. Names the return fields and describes the action with specific verb and resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to call when user asks if updates exist or proactively when tools fail due to stale bridge. Provides clear context.
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 burden of behavioral disclosure. It reveals the return shape ({status, headers, body}), default localhost-only scope, and the rarity of allow_remote. However, it could mention rate limits or permissions for making external requests, but the explicit security constraint (localhost default) compensates, making it mostly transparent.
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, well-structured paragraph of 4 sentences. It front-loads the main action (HTTP request) and follows with specific use cases and constraints. Every sentence adds value without redundancy, making it concise and easily scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema or annotations, the description covers all necessary aspects: return format, typical use cases, security scope, and limitation (not general-purpose). It is sufficient for an agent to understand and correctly invoke the tool, addressing the complexity of making an HTTP request.
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 schema has 0% property descriptions, so the description must compensate. It provides meaning for url (example localhost URLs), method (implicit via enum), and allow_remote (rare). Headers and body are not elaborated beyond the schema, but the overall context of making an HTTP request gives them implicit meaning. The description adds value but does not fully detail all parameters.
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 core function: making an HTTP request and returning status, headers, body. It distinguishes itself from sibling tools like mock_endpoint or peek_openapi by providing specific use cases (testing mocks, inspecting admin API, verifying endpoints). This satisfies the specific verb+resource requirement and differentiates from alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly outlines when to use the tool (demonstrate a mock, inspect admin API, verify mock endpoint) and when not to (the bridge is not a general-purpose HTTP client, allow_remote is rare). This provides clear context and exclusions, guiding the agent to appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully bears the burden. It describes the destructive nature (wiping all mocks and stopping server), provides an equivalent command (`rm -rf ~/.cache/mockzilla-mcp/mocks` plus `stop_locally`), and explicitly states what it does NOT affect ('Does not touch the mockzilla CLI binary or other bridge state'), offering full transparency.
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, well-structured paragraph. It front-loads the primary action, includes a functional equivalent, and adds clarifying statements. Every sentence serves a purpose, with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description provides complete context: what the tool does, how it relates to siblings (`mock_endpoint`, `stop_locally`), its effects, and its limitations. Nothing essential is missing for correct invocation.
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 schema coverage is 100%. The description adds meaning by explaining the effect, but since no parameters exist, it cannot add parameter-level detail. Baseline 4 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's action: 'Wipe ALL mocks created via `mock_endpoint` and stop the managed server.' It uses a specific verb ('Wipe') and resource ('ALL mocks'), and distinguishes itself from sibling tools like `mock_endpoint` (which creates) and `stop_locally` (only stops server).
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 explicitly says 'Use when the user wants to start fresh,' providing a clear usage context. It does not explicitly state when not to use, but the context is sufficient to infer that this is for complete cleanup; alternatives like `stop_locally` exist for partial actions.
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?
No annotations provided, but the description is self-sufficient: it describes a read-only listing operation with no side effects. It does not contradict any annotations. The behavior is obvious from 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?
Two sentences: first states the purpose with examples, second provides usage guidance. No wasted words. Front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and no output schema, the description fully covers what the tool does, when to use it, and how it relates to siblings. No missing information.
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 input schema has 0 parameters with 100% coverage (empty). The description adds meaning beyond the schema by explaining the purpose, examples, and contextual usage. Baseline for 0 params is 4, and the description meets it well.
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 it lists available mockzilla doc topics with examples (e.g., 'usage/portable', 'middleware'), and distinguishes it from sibling tools by explaining when to use each (search and read).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states to call once at the start of a session involving non-trivial mockzilla usage, and then suggests calling `mockzilla_docs_search` or `mockzilla_docs_read` for specific topics. Provides clear when-to-use and next steps.
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 covers key behaviors: starts a server, returns {url, port, pid, services}, is ephemeral, runs only one server at a time, and requires pairing with stop_locally. Lacks mention of permissions or resource cleanup, but overall transparent.
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 informative but somewhat lengthy, containing multiple paragraphs and examples. It is well-structured with a clear first sentence, then details and usage guidance, but could be more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (local server, multiple APIs, output details) and lack of output schema, the description fully explains the behavior, output format, cleanup, and edge cases like well-known APIs. No gaps identified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds significant value: explains that input can be a single path/directory/URL or an array, each becoming a service mounted at /<service>/. Provides examples of well-known API URLs and cautions against using catalog IDs.
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 starts a mockzilla portable mock server locally, specifying it can serve multiple APIs from spec paths or URLs. It distinguishes itself from sibling deploy_mock_from_* tools by emphasizing ephemeral local usage.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to prefer this over deploy_mock_from_* when user says 'try locally', 'experiment', or 'play with'. Provides guidance on stopping current server and restarting with all APIs. Also explains how to handle well-known APIs without a URL by recalling public OpenAPI specs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description fully discloses behavior: stops server, takes no arguments, returns {stopped: bool, pid?, reason?}. No contradictions.
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?
Two concise sentences, each providing essential information. Action is front-loaded. No extraneous text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description explicitly states return format and server uniqueness, making it complete for agent usage.
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?
No parameters, so baseline is 4. Description adds context that it takes no arguments and only one server exists, which is helpful 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?
Clearly states the tool stops the mockzilla server started by serve_locally, specifying the action and resource. Distinguishes from sibling tools by explicitly mentioning the server it stops.
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?
Implies usage context: use after serve_locally when a local server is running. Notes there is only one server. Does not explicitly state when not to use, but the simplicity of the tool makes it adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description fully discloses behavioral traits: writes to a managed directory, (re)starts a shared mockzilla server, accumulates endpoints, handles path placeholders as literal directory names, and is mutually exclusive with serve_locally. No annotation contradiction.
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 detailed and front-loaded with essential info, but slightly verbose. Every sentence adds value, though could be trimmed slightly. Examples aid clarity but lengthen text.
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?
Covers core behaviors and side effects thoroughly, but does not explicitly state what the tool returns (e.g., confirmation, URL). With no output schema, a brief mention of return value would improve completeness for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds significant meaning beyond the input schema: explains each parameter with examples, default behavior, and nuances (e.g., response type inference, path placeholders). The description compensates for any schema gaps, with 60% schema description 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 clearly states the tool's purpose: 'Quickly mock a single HTTP endpoint without writing an OpenAPI spec.' It uses specific verbs and resources, and distinguishes from siblings like serve_locally and clear_mock_endpoints by explaining accumulation and mutual exclusivity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use guidance, including parameter defaults and path handling. Warns against prepending segments, explains placeholders, and contrasts with serve_locally ('Mutually exclusive... stop any ad-hoc server first'). Includes examples for correct usage.
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?
No annotations provided, but description reveals read-only operation, input types, and that it returns summary not full spec. Could mention side effects, but none exist.
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?
Two sentences, front-loaded with main action and return value, no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple single-parameter tool with no output schema, the description covers all essential information: purpose, input format, and return structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 0% coverage, but description adds critical semantics: input can be file path or public https URL, which fully clarifies the parameter.
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?
Clearly states the tool summarizes an OpenAPI spec without serving it, lists return fields, and contrasts with serve/deploy siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use ('before deciding whether to serve or deploy it'), and implies alternatives (serve_locally, call_endpoint).
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:

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

Score Badge

Copy to your README.md:

[![mockzilla-mcp MCP server](https://glama.ai/mcp/servers/mockzilla/mockzilla-mcp/badges/score.svg)](https://glama.ai/mcp/servers/mockzilla/mockzilla-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/mockzilla/mockzilla-mcp'

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