crypto-reverse-mcp
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@crypto-reverse-mcpdetect the encryption algorithm in this JS code"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
crypto-reverse-mcp
The missing "last mile" of JS reverse engineering. A Model Context Protocol (MCP) server that detects cryptographic algorithms, identifies obfuscation, reconstructs standalone implementations, generates SDKs, and bypasses anti-debugging — designed to complement browser-debugging MCP servers like js-reverse-mcp.
English | 中文
Why this exists
Existing JS-reverse MCP servers focus on browser debugging (breakpoints, network capture, script analysis). They help you find the encryption function. But they don't answer:
What algorithm is this? (AES? SM2? custom?)
Where does the key come from? (static? derived? from server?)
How do I reproduce it in Python?
How do I generate a complete SDK?
How do I bypass the anti-debugging that blocks my breakpoints?
crypto-reverse-mcp fills these gaps. It's a complement, not a replacement — pair it with js-reverse-mcp for the full workflow:
js-reverse-mcp: open page → find script → set breakpoint → capture I/O
crypto-reverse-mcp: identify algorithm → extract key → reconstruct Python → generate SDKRelated MCP server: PCM
Features
Tool | What it does |
| Identify AES/DES/RSA/SM2/SM3/SM4/HMAC/MD5/SHA + key/IV source + cipher mode |
| Detect webpack/JSFuck/AAEncode/obfuscator.io/packer/control-flow-flattening |
| Find S-boxes, initial hash values, round constants, curve parameters |
| Generate standalone Python/Node implementation from JS source + samples |
| Produce complete Python/Node/Go SDK with signing, login, error handling |
| Generate injection scripts to neutralize debugger loops, devtools detection, timing checks |
Quick Start
Claude Desktop / Cursor / VS Code Copilot
{
"mcpServers": {
"crypto-reverse": {
"command": "npx",
"args": ["-y", "crypto-reverse-mcp@latest"]
}
}
}Claude Code
claude mcp add crypto-reverse -- npx -y crypto-reverse-mcp@latestCodex CLI
codex mcp add crypto-reverse -- npx -y crypto-reverse-mcp@latestVS Code Copilot
code --add-mcp '{"name":"crypto-reverse","command":"npx","args":["-y","crypto-reverse-mcp@latest"]}'Requirements
Node.js 18+
Tool Details
detect_crypto
Input: JS source code (string)
Output: List of detected crypto usages with:
Algorithm name (AES, RSA, SM2, SM3, SM4, MD5, SHA-1, SHA-256, HMAC, PBKDF2, etc.)
Category (symmetric / asymmetric / hash / mac / kdf / encoding)
Library (CryptoJS, JSEncrypt, sm-crypto, node-forge, jsrsasign, WebCrypto, Node crypto)
Location (line:column) + code snippet
Confidence score (0-100%)
Key source (static string / variable / localStorage / cookie / app config)
IV source (for symmetric ciphers)
Cipher mode (CBC/ECB/GCM/CTR/CFB/OFB)
Padding (Pkcs7/ZeroPadding/NoPadding)
Detection methods:
Library API patterns (50+ regex patterns)
Web Crypto API / Node crypto module calls
Crypto constants (AES S-box, SHA-256 initial hash, SM3 IV, SM4 S-box, DES S-box, etc.)
Function name heuristics
identify_obfuscation
Input: JS source code
Output: Obfuscation type + confidence + unpack strategy
Detects: webpack-bundle, obfuscator.io, JSFuck, AAEncode, JJEncode, dean-edwards-packer, eval-loader, control-flow-flattening, string-array, dead-code-injection, minified, terser-minified
Each detection includes:
Confidence score
Evidence (what pattern matched)
Unpack hint (how to approach unpacking)
Deobfuscation strategy (step-by-step)
Recommended tools
extract_crypto_constants
Input: JS source code
Output: List of found crypto constants
Detects:
AES S-box / Inverse S-box / Rcon
SHA-256 initial hash values + round constants
SHA-1 initial hash values
MD5 initial values + T-constants
SM3 IV + Tj constants
SM4 S-box + FK + CK constants
DES S-box + IP permutation
SM2 / NIST P-256 curve parameters
CRC32 polynomial
Base64 alphabet
reconstruct_algorithm
Input: JS source code + optional input/output samples + target language
Output: Self-contained Python or Node implementation
How it works:
Detects algorithm type from source patterns
Extracts parameters (key, IV, mode, padding)
Generates implementation using standard libraries (pycryptodome, gmssl)
If samples provided, includes verification code
Supported algorithms: AES (CBC/ECB/GCM/CTR), DES, TripleDES, MD5, SHA-1, SHA-256, HMAC-SHA256, HMAC-MD5, RSA (PKCS1), SM2, SM3, SM4, Base64
generate_sdk
Input: API specification (URL, method, headers, sign spec, login spec) + target language
Output: Complete SDK file with:
Request construction with auto-signing
Crypto signature generation (HMAC/MD5/custom)
Login flow (with password encryption hook)
Error handling
Usage example
Languages: Python (requests), Node.js (http/https), Go (net/http)
bypass_anti_debug
Input: JS source code (optional) + techniques to bypass + output format
Output: Bypass injection script
Techniques:
debugger_loop— Neutralizedebuggerstatements in loopssetInterval_debugger— BlocksetIntervalcallbacks containingdebuggerdevtools_window_size— FixouterWidth - innerWidthdetectiondevtools_console_access— Prevent console object inspectiontiming_check— CapDate.now()/performance.now()deltasconsole_getter_trap— UndoObject.defineProperty(console, ...)function_toString_check— MakeFunction.toString()return native code
Output formats: inject_script (Tampermonkey/snippet), fiddler_rule (Fiddler OnBeforeResponse), chrome_devtools_snippet (DevTools Snippets)
Typical Workflow
1. [js-reverse-mcp] new_page → navigate to target site
2. [js-reverse-mcp] search_in_sources for "encrypt" / "sign"
3. [crypto-reverse-mcp] detect_crypto on found script → identify AES-CBC
4. [crypto-reverse-mcp] extract_crypto_constants → confirm S-box present
5. [js-reverse-mcp] set_breakpoint_on_text → capture input/output
6. [crypto-reverse-mcp] reconstruct_algorithm with samples → get Python code
7. [crypto-reverse-mcp] generate_sdk → complete API SDK
8. [crypto-reverse-mcp] bypass_anti_debug → if blocked by debuggerLocal Development
git clone https://github.com/crypto-reverse/crypto-reverse-mcp.git
cd crypto-reverse-mcp
npm install
npm run build
npm startDebug with MCP Inspector
npx @modelcontextprotocol/inspector node build/src/index.jsTest stdio communication
echo '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-06-18","capabilities":{},"clientInfo":{"name":"test","version":"1.0.0"}}}' | node build/src/index.jsConfiguration
No configuration required. All tools are stateless and work offline.
Comparison with other JS-reverse MCP servers
Feature | js-reverse-mcp | js-reverse-pro-mcp | mcp-reverse-server | crypto-reverse-mcp |
Browser debugging | ✅ | ✅ | ✅ | ❌ |
Breakpoints | ✅ | ✅ | ✅ | ❌ |
Network capture | ✅ | ✅ | ✅ | ❌ |
Hook framework | ❌ | ✅ | ❌ | ❌ |
Deobfuscation | ❌ | ✅ (Babel) | ✅ (AST) | ⚠️ (identify only) |
JSVMP analysis | ❌ | ❌ | ✅ | ❌ |
Crypto algorithm detection | ❌ | ⚠️ (keyword scan) | ⚠️ | ✅ (50+ patterns) |
Crypto constants extraction | ❌ | ❌ | ❌ | ✅ (S-box, IV, curves) |
Algorithm reconstruction | ❌ | ❌ | ❌ | ✅ (Python/Node) |
SDK generation | ❌ | ❌ | ❌ | ✅ (Python/Node/Go) |
Anti-debug bypass | ❌ | ❌ | ❌ | ✅ (7 techniques) |
Obfuscation identification | ❌ | ❌ | ❌ | ✅ (11 types) |
Use together for maximum coverage. crypto-reverse-mcp is designed to be complementary.
Roadmap
v0.2:
trace_crypto_chain— trace encryption from ciphertext back to plaintextv0.2: Improved minified code analysis (variable flow tracking)
v0.3: WASM crypto module detection
v0.3: Custom algorithm identification via I/O analysis
v0.4: Java SDK generation
v0.4: RPC-style API SDK generation (gRPC, GraphQL)
License
MIT
Available Tools
6 toolsbypass_anti_debugA
Generate anti-debugging bypass scripts for common anti-debug techniques. Detects and generates bypass for: debugger statement loops, setInterval debugger, devtools detection (window size, console access, Function.toString), timing checks, console.log getter traps, and CodeMirror/eruda detection. Input: JS source code or technique name. Returns bypass injection script + injection instructions.
| Name | Required | Description | Default |
|---|---|---|---|
| source | No | JS source code to analyze (if empty, generate universal bypass) | |
| techniques | No | Specific techniques to bypass (default: all) | |
| outputFormat | No | Output format (default: inject_script) |
TDQS
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.
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.
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.
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.
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.
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.
detect_cryptoA
Detect cryptographic algorithms used in JavaScript source code. Identifies AES/RSA/SM2/SM3/SM4/HMAC/MD5/SHA family algorithms with evidence, key/IV source tracking, and cipher mode. Input: JS source code string. Returns list of detected crypto usages with algorithm type, location (line/col), evidence snippet, key source, IV source, and mode (CBC/ECB/GCM/CTR etc).
| Name | Required | Description | Default |
|---|---|---|---|
| source | Yes | JavaScript source code to analyze | |
| options | No | Detection options |
TDQS
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.
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.
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.
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.
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.
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.
extract_crypto_constantsA
Extract cryptographic constants from JS source code. Identifies S-boxes (AES/DES), initial hash values (SHA-256/SHA-1/MD5/SM3), round constants, elliptic curve parameters (SM2/NIST curves), magic numbers, and known crypto constant arrays. Input: JS source code. Returns list of found constants with their crypto algorithm association and location.
| Name | Required | Description | Default |
|---|---|---|---|
| source | Yes | JavaScript source code to analyze |
TDQS
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.
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.
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.
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.
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.
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.
generate_sdkA
Generate a ready-to-use SDK (Python/Node/Go) from a reversed API contract. Given endpoint URL, HTTP method, headers, body template, and the signature/encryption algorithm spec, produce a complete SDK file with: request construction, crypto signing, error handling, and usage example. Input: API spec (url, method, sign algorithm description, params). Returns SDK code in requested language.
| Name | Required | Description | Default |
|---|---|---|---|
| apiSpec | Yes | ||
| language | No | SDK output language (default: python) |
TDQS
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.
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.
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.
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.
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.
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.
identify_obfuscationA
Identify the obfuscation/packing technique used in JavaScript code. Detects webpack bundles, AAEncode, JJEncode, JSFuck, obfuscator.io, JavaScript obfuscator, babel minified, packer (Dean Edwards), UPX-style, eval-based loaders, and control-flow flattening. Input: JS source code. Returns obfuscation type, confidence, unpack hints, and recommended deobfuscation strategy.
| Name | Required | Description | Default |
|---|---|---|---|
| source | Yes | JavaScript source code to analyze |
TDQS
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.
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.
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.
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.
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.
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.
reconstruct_algorithmA
Reconstruct a standalone implementation of a cryptographic algorithm from JS source + captured input/output samples. Given the original JS code and (optionally) sample input→output pairs, generate a self-contained Python implementation that reproduces the same transformation. Supports common AES/RSA/HMAC/MD5/SHA/SM2/SM3/SM4 patterns. Input: source code, optional samples (array of {input, output} pairs), target language (python/node). Returns reconstructed code + verification notes.
| Name | Required | Description | Default |
|---|---|---|---|
| source | Yes | JS source code containing the crypto function | |
| samples | No | Sample input/output pairs for verification | |
| functionName | No | Name of the target function to reconstruct (if known) | |
| targetLanguage | No | Output language (default: python) |
TDQS
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.
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.
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.
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.
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.
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.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
6 tool updates
v0.1.0- First observed
bypass_anti_debug - First observed
detect_crypto - First observed
extract_crypto_constants - First observed
generate_sdk - First observed
identify_obfuscation - First observed
reconstruct_algorithm
TDQS
Scored across 6 tools
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.
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.
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.
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.
Maintenance
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