MCP HTTP Requests

by godzeo

Overview Schema Related Servers Score Discussions

Python

Hybrid

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose: seven tools correspond to specific HTTP methods (GET, POST, etc.), while the eighth tool (http_raw_request) is explicitly for security testing with absolute precision. There is no ambiguity or overlap between the standard HTTP method tools, and the security tool is clearly differentiated by its specialized function.
Naming Consistency5/5
All tool names follow a consistent snake_case pattern with the prefix 'http_' followed by the HTTP method name (e.g., http_get, http_post) or a descriptive term (http_raw_request). This uniformity makes the tools easily predictable and readable, with no deviations in naming conventions.
Tool Count5/5
With 8 tools, the set is well-scoped for an HTTP requests server. It covers all standard HTTP methods (GET, POST, PUT, DELETE, PATCH, HEAD, OPTIONS) plus a specialized security testing tool, which is a reasonable and complete set for the domain without being excessive or insufficient.
Completeness5/5
The tool surface is complete for the domain of HTTP requests. It provides full CRUD-like coverage with all standard HTTP methods, and the inclusion of http_raw_request adds specialized functionality for security testing, ensuring no gaps in core operations or advanced use cases.
Average 3.1/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
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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

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 mentions logging ('All requests logged'), which adds some context, but fails to address critical traits like error handling, response format, authentication needs, or rate limits. For a network tool with zero annotation coverage, this is inadequate.
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 (one sentence) and front-loaded with the core purpose. However, the phrase 'with full support' is vague and could be trimmed for clarity, slightly reducing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 5 parameters with 0% schema coverage, no annotations, no output schema, and sibling tools, the description is incomplete. It lacks details on parameter usage, behavioral expectations (e.g., response handling), and differentiation from siblings, making it insufficient for effective tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning parameters are undocumented in the schema. The description lists parameters (headers, cookies, body, timeout) but provides no semantic details—e.g., what format headers/cookies should be in, what body content is allowed for GET, or timeout units. It doesn't compensate for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs an 'HTTP GET request' with specific capabilities (headers, cookies, body, timeout), which is a specific verb+resource combination. However, it doesn't explicitly distinguish this from its sibling tools (http_delete, http_post, etc.) beyond the GET method, missing differentiation that would earn a 5.
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 like http_post or http_raw_request. It mentions 'full support' but doesn't specify scenarios where GET is appropriate (e.g., retrieving data vs. sending data), leaving the agent without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It mentions that 'All requests logged,' which adds some context about side effects. However, it doesn't cover critical aspects like authentication requirements, rate limits, error handling, or what 'DELETE' actually does to the target resource (destructive nature).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose. Every phrase ('HTTP DELETE request,' 'full support,' 'All requests logged') contributes meaningful information without waste.
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 5-parameter tool with no annotations and no output schema, the description is incomplete. It lacks details on authentication, error responses, the destructive nature of DELETE, and how to interpret results. The logging mention is helpful but insufficient for full contextual 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 description coverage is 0%, so the description must compensate. It lists 'headers, cookies, body, timeout' as supported features, which maps to 4 of the 5 parameters (missing 'url'). This adds some meaning beyond the bare schema, but doesn't explain parameter purposes, formats, or constraints in detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs an 'HTTP DELETE request' with 'full support' for various HTTP features, which is a specific verb+resource combination. However, it doesn't explicitly distinguish this DELETE operation from its sibling tools (GET, HEAD, OPTIONS, etc.) beyond the HTTP method name.
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 DELETE request versus alternatives like http_raw_request or other HTTP methods. It mentions 'full support' but doesn't specify use cases, prerequisites, or exclusions for DELETE 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?
No annotations are provided, so the description carries full burden. It mentions logging and full support for features, but lacks details on error handling, response format, rate limits, authentication needs, or what 'full support' entails. This is inadequate for a network tool with potential side effects.
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, efficient sentence with no wasted words. It front-loads the core action (HTTP HEAD request) and lists key features directly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and 0% schema coverage, the description is incomplete. It omits critical details like response behavior, error cases, and practical usage context, making it insufficient for safe and effective tool invocation.
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 0%, so the description must compensate. It lists parameters (headers, cookies, timeout) and implies a URL, but doesn't explain their purposes, formats, or constraints (e.g., timeout units, cookie structure). This adds minimal value beyond the schema's property names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs an 'HTTP HEAD request' with specific features (headers, cookies, timeout) and mentions logging. It distinguishes from siblings by specifying the HTTP method (HEAD vs GET/POST/etc.), but doesn't explicitly differentiate the purpose beyond the method name.
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 HEAD vs other HTTP methods (like GET for retrieving body content) or alternatives. The description mentions features but not typical use cases (e.g., checking resource existence, headers without body).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that 'All requests logged', which is a useful behavioral trait beyond the basic operation. However, it lacks details on error handling, response format, authentication needs, or rate limits, leaving gaps for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('HTTP OPTIONS request') and lists key features. It avoids unnecessary words, though it could be slightly more structured (e.g., separating features with commas or bullets).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It mentions logging but omits critical context like response handling, error scenarios, or typical outputs. For a 4-parameter tool with siblings, more detail is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions 'headers, cookies, timeout' but doesn't explain their purposes, formats, or interactions. For example, it doesn't clarify what 'timeout' units are (seconds), how cookies are formatted, or provide examples. This adds minimal value beyond the schema's property names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs an 'HTTP OPTIONS request' with specific features (headers, cookies, timeout), which is a specific verb+resource. It distinguishes from siblings by specifying the HTTP method (OPTIONS) versus DELETE, GET, HEAD, etc., though it doesn't explicitly contrast functionality beyond the method name.
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 like http_get or http_raw_request. It mentions 'full support' but doesn't explain typical use cases for OPTIONS requests (e.g., CORS preflight, server capabilities) or when other HTTP methods might be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It mentions logging behavior ('All requests logged') which is valuable, but fails to disclose critical behavioral traits like authentication requirements, error handling, rate limits, or what the response format looks like. For a network operation tool with zero annotation coverage, this leaves significant gaps.
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 efficiently structured in a single sentence that communicates the core functionality and key features. It's appropriately sized for the tool's complexity, though it could be slightly more front-loaded by starting with the primary purpose before listing capabilities.
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 network operation tool with 5 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what the tool returns, error conditions, authentication needs, or practical usage scenarios. The logging mention is helpful but doesn't compensate for the overall lack of context needed to use this tool effectively.
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?
With 0% schema description coverage, the description doesn't add any parameter-specific information beyond what's implied by the tool name. It mentions 'headers, cookies, body, timeout' in a list but doesn't explain their purpose, format, or constraints. The baseline is 3 since the schema provides complete parameter definitions despite lacking descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs an 'HTTP PATCH request' with specific capabilities (headers, cookies, body, timeout) and mentions logging. It distinguishes itself from siblings by specifying the HTTP method (PATCH), but doesn't explicitly differentiate from other HTTP method tools beyond the method name.
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 like http_post or http_put. It mentions 'full support' but doesn't explain when PATCH is appropriate compared to other HTTP methods, leaving the agent to infer usage from the method 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 full burden but only mentions logging ('All requests logged'). It lacks critical behavioral details like authentication requirements, error handling, rate limits, or what 'logged' entails (e.g., where logs are stored). This is insufficient for a mutation tool with zero annotation coverage.
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, efficient sentence with zero waste. It front-loads the core purpose and includes key features without redundancy, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with 5 parameters, 0% schema coverage, no annotations, and no output schema, the description is inadequate. It misses details on response format, error cases, security implications, and practical usage, leaving significant gaps in contextual 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 description coverage is 0%, so the description must compensate. It lists parameters (headers, cookies, body, timeout) but doesn't explain their semantics, formats, or interactions beyond naming them. This adds minimal value over the schema, meeting the baseline for low coverage without fully compensating.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('HTTP POST request') and scope ('with full support (headers, cookies, body, timeout)'), distinguishing it from siblings by specifying POST method. However, it doesn't explicitly contrast with other HTTP methods like GET or PUT, which would make it a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like http_put or http_patch is provided. The description mentions 'full support' but doesn't specify scenarios where POST is appropriate over other HTTP methods, leaving usage context implied at best.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It adds that 'All requests logged', which is useful context about side effects. However, it lacks critical details: whether this is idempotent (typical for PUT), authentication requirements, error handling, rate limits, or what the response contains. For a mutation tool with zero annotation coverage, this is insufficient.
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, efficient sentence with zero waste. It's front-loaded with the core purpose and includes key features without redundancy. Every word earns its place, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (HTTP mutation tool with 5 parameters), no annotations, no output schema, and 0% schema coverage, the description is incomplete. It mentions logging but omits essential context: response format, error behavior, idempotency, authentication, and typical use cases. This leaves the agent under-informed for safe and effective tool invocation.
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 0%, so the description must compensate. It lists parameters (headers, cookies, body, timeout) in parentheses, adding some meaning beyond the schema's property names. However, it doesn't explain parameter purposes (e.g., timeout in seconds, body format) or constraints, leaving significant gaps. The baseline is lowered due to poor schema coverage, but the description provides minimal compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs an 'HTTP PUT request' with 'full support (headers, cookies, body, timeout)', which specifies the verb (PUT request) and resources (HTTP endpoints). It distinguishes from siblings by mentioning PUT specifically, though it doesn't explicitly contrast with other HTTP methods like POST or PATCH.
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 like http_post or http_patch. It mentions 'full support' but doesn't explain typical PUT use cases (e.g., updating resources) or prerequisites, leaving the agent to infer usage from the HTTP method name alone.
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 provided, the description carries full burden and excels. It discloses critical behavioral traits: preserves all characters exactly (no truncation/encoding), logs all requests/responses to a specific directory (~/mcp_requests_logs/), and guarantees zero modifications to input. This provides essential context about security implications and side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized but not optimally structured. It uses emojis and formatting that may not parse well in all contexts. While information-dense, it could be more front-loaded with the core purpose before details. Every sentence earns its place, but the presentation could be more streamlined for agent consumption.
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 complexity (security-critical HTTP tool with 6 parameters, no annotations, no output schema), the description does well. It covers behavioral guarantees, logging, use cases, and precision characteristics. However, it doesn't mention error handling, response format expectations, or authentication requirements that might be relevant for a raw HTTP tool.
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?
Schema description coverage is 0%, so the description must compensate. While it doesn't explicitly name parameters, it provides crucial semantic context for several: explains how headers/cookies/body parameters are handled (preserved exactly), mentions special character handling relevant to all string parameters, and implies timeout behavior through the precision focus. However, it doesn't cover all 6 parameters explicitly.
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 'sends HTTP requests with ABSOLUTE PRECISION' and emphasizes it's for 'security testing'. It distinguishes from sibling tools (http_get, http_post, etc.) by highlighting its raw, unmodified request handling rather than being method-specific. The description goes beyond the name/title to explain the specific behavior.
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 when to use this tool: 'Perfect for: all kinds of security vulnerability testing, testing like SQL injection, XSS, CSRF, authentication bypass, parameter pollution'. It also implicitly distinguishes from sibling tools by emphasizing raw precision rather than convenience methods. The description provides clear context about appropriate use cases.
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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