crypto-reverse-mcp

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool targets a distinct aspect of JavaScript reverse engineering: crypto detection, obfuscation identification, algorithm reconstruction, anti-debug bypass, SDK generation, and constant extraction. There is no overlap or ambiguity.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern (detect_crypto, identify_obfuscation, reconstruct_algorithm, etc.), making them predictable and easy for an agent to navigate.
Tool Count5/5
With 6 tools, the set is well-scoped for a specialized crypto-reverse MCP server. Each tool serves a clear purpose without unnecessary bloat or deficiency.
Completeness4/5
The tool surface covers core reverse engineering workflows: detection, identification, reconstruction, bypass, and SDK generation. A minor gap is the lack of a deobfuscation tool that actually transforms obfuscated code (beyond identification), but the set is otherwise complete for its stated domain.
Average 4/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 9 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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 provided, so the description carries the full burden. It describes the types of constants found and the output but does not disclose limitations, potential false positives, or performance considerations. The description is adequate but not detailed.
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 (two sentences plus a list) and front-loaded with the main action. Every sentence is relevant, and there is no redundant information. It is well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single parameter and no output schema, the description covers input sufficiently but lacks details about the return format (e.g., whether it's a list of objects with specific fields). The mention of 'list of found constants with their crypto algorithm association and location' is helpful but could be more explicit.
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 'source' exists, with a description in the schema. The tool description adds 'Input: JS source code' which repeats the schema's description. Since schema coverage is 100%, the description adds marginal value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: extracting cryptographic constants from JS source code. It lists specific types of constants (S-boxes, hash values, etc.) and distinguishes itself from siblings like detect_crypto and reconstruct_algorithm by focusing on constant extraction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions input and output but does not provide explicit guidance on when to use this tool versus alternatives (e.g., 'Use after detect_crypto' or 'For full reconstruction, see reconstruct_algorithm'). The context is clear but lacks explicit when-to-use/when-not-to-use.
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 the full burden. It positively describes the output (complete SDK with error handling) but fails to disclose limitations, such as potential need for manual adjustments, rate limits, or dependency on the accuracy of the reversed contract. The description does not mention any destructive or privacy implications.
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 (3-4 sentences) and front-loaded with the primary purpose. It uses clear structure: general statement, list of inputs, description of output. However, it could be slightly more streamlined by avoiding redundancy with schema descriptions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of the nested input schema and the lack of an output schema, the description provides a reasonable overview but lacks specifics on how the SDK code is returned (e.g., as a string, file download) and does not cover error scenarios or limitations. For a tool generating complete code, more detail on the output format would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions key input fields (url, method, headers, body template, sign algorithm) that mirror the schema properties. However, it adds little beyond what the schema already provides (e.g., it does not explain the nested signSpec or loginSpec in detail). With schema description coverage at 50% and the parameter descriptions in the schema being detailed, the description adds marginal value for understanding parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a ready-to-use SDK from a reversed API contract, specifying supported languages (Python, Node, Go) and key features like request construction, crypto signing, error handling, and usage examples. It effectively distinguishes itself from sibling tools (e.g., detect_crypto, identify_obfuscation) which focus on analyzing cryptographic aspects rather than generating client code.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you have an API spec (url, method, sign algorithm, params) but does not explicitly provide guidance on when to use this tool versus alternatives or when not to use it. There are no exclusion criteria or mention of prerequisites beyond the input schema.
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 discloses core behavior (detection, output format) but omits potential limitations (e.g., false positives, performance with large code, handling of dynamic imports). It does not contradict any annotations.
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 introduces the purpose, second details the output. Extremely concise, front-loaded, with no filler. Every sentence adds value.
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?
The description covers input, output format, and key details (algorithm families, evidence). Given the moderate complexity (2 params, nested object) and no output schema, it provides sufficient context. Could mention handling of edge cases or error conditions for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents parameters. The description reiterates the input as 'JS source code string' but adds no new semantic details beyond what the schema provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool detects cryptographic algorithms in JavaScript source code, listing specific algorithm families (AES, RSA, SM2, etc.) and the extracted evidence (location, key source, IV, mode). This specificity distinguishes it from sibling tools like 'identify_obfuscation' and 'extract_crypto_constants'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when needing to identify crypto usage in JS code but provides no explicit guidance on when to prefer this tool over siblings like 'extract_crypto_constants' or 'reconstruct_algorithm'. No exclusion criteria or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It lists handled techniques and explains inputs/outputs. However, it lacks disclosure of potential side effects, permissions, or resource usage. No contradiction with annotations.
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 relatively concise with two sentences and a list of techniques. It is front-loaded with the main purpose. Minor redundancy in listing techniques again in schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description mentions the return comprises a bypass script and injection instructions, but does not specify the precise format (e.g., string, object). Parameter descriptions are adequate but could be more detailed. Somewhat complete but leaves gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with each parameter described. The description adds context about default behavior (e.g., universal bypass if empty) but does not significantly clarify parameter meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates anti-debugging bypass scripts for specific techniques, and lists those techniques. It uses a specific verb and resource (generate bypass scripts) and distinguishes from siblings which focus on crypto and obfuscation.
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 explains the input (JS source or technique name) and output (bypass script + instructions), implying when to use (when anti-debugging is present). However, it does not explicitly state when not to use or provide alternatives, though siblings are unrelated.
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 the full burden. It describes what the tool detects, that input is JS source, and returns obfuscation type, confidence, unpack hints, and deobfuscation strategy. It implies read-only analysis but does not explicitly state non-destructive behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of two sentences. The first sentence states purpose and lists examples, the second specifies input and output. No waste; every word earns its place.
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 single parameter with full schema coverage, no output schema, and unrelated sibling tools, the description provides everything needed: what the tool does, required input, and output structure. It is complete and leaves no ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter 'source' (described as 'JavaScript source code to analyze'). The description repeats this nearly verbatim ('Input: JS source code'), adding minimal new semantic value beyond stating the input context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: identifying obfuscation/packing techniques in JavaScript code. It lists specific techniques (webpack, AAEncode, JJEncode, etc.), which distinguishes it from sibling tools focused on crypto, anti-debug, etc.
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 implies usage when analyzing JS code for obfuscation, and siblings are unrelated (crypto, anti-debug), so it's sufficiently clear. However, it lacks explicit when-not-to-use or alternative-tool guidance, which prevents a 5.
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, so description carries full burden. It explains it generates self-contained Python implementation, supports common patterns, returns code + verification notes. Missing details on error handling or time limits, but adequate for a reconstruction 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?
One paragraph with front-loaded purpose. Every sentence adds value, no waste. Efficient and clear.
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?
No output schema, but description states return value (reconstructed code + verification notes). Parameters well described. Could mention verification process more, but sufficient for the complexity.
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?
100% schema coverage, so baseline is 3. Description adds value by explaining the role of samples as optional verification and target language options, beyond the schema descriptions.
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?
Clear verb 'reconstruct' and resource 'cryptographic algorithm' with specific inputs (JS source, samples). Distinguishes from siblings like detect_crypto (detection) and extract_crypto_constants (extraction).
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?
States when to use: given JS source and optionally samples to generate Python implementation. Implies context but does not explicitly exclude alternatives (e.g., if only detection needed, use detect_crypto).
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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