xingce-solver
The xingce-solver server is an assistive toolkit for LLM agents to tackle Chinese civil service exam (行测) questions. It provides structured routing, method retrieval, solving scaffolds, and constrained prompt generation—without directly answering questions itself.
Question Routing (
route_xingce_question): Classify a question into the appropriate exam module (e.g., 资料分析, 逻辑判断, 图形推理) with confidence scores and recommended analysis tracks; supportsmodule_hintandsection_contextfor guided routing.Lightweight Classification (
classify_question): Quickly route a question stem to preliminary modules and relevant method cards via keyword matching.Method Card Retrieval (
get_method_card,search_methods): Fetch full method cards by ID or search the 292-card knowledge base by keyword, with optional module filtering.Source Reference Lookup (
get_source_reference): Retrieve source files, page references, confidence levels, and review flags for a given method.Structured Solving Drafts (
solve_data_analysis,solve_logic_reasoning): Build step-by-step solving drafts for 资料分析 and 逻辑判断 questions that an LLM can follow to produce a final answer.Methodological Scaffolds: Read-only step-by-step guides for six modules—Graphic Reasoning, Definition Judgement, Analogy Reasoning, Logic Analysis, Quantity Relation, and Verbal Reasoning—covering observation order, checklists, response templates, and uncertainty policies.
Prompt Composition (
compose_xingce_analysis_prompt,compose_xingce_answer_prompt): Generate structured analysis or conservative answer prompts incorporating routing results, scaffold summaries, strict output schemas, and safety contracts.Safety Gates: Hard-coded checks block answering when visual content or materials are missing, routing is uncertain, or answer mode is disabled—returning a block reason instead of a guess.
Click on "Install 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., "@xingce-solver资料分析:2020年收入132亿元,同比增10%,求2019年收入?"
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.
Huasheng Shisan · Civil Service Exam Problem-Solving MCP Assistant
📚 Based on the Huasheng Shisan civil service exam knowledge base, 442 method cards covering four major modules: data analysis, quantitative relations, logical reasoning, and verbal comprehension. Paired with AI assistants (Claude Desktop, etc.), you can solve problems intelligently anytime, anywhere.
🚀 One-Minute Quick Start
Method 1: Let the Agent Install It for You (Easiest)
If you're a user of AI coding tools like Claude Code, Codex CLI, Cursor, Windsurf, just send the following sentence to it:
"Help me install this MCP server: https://github.com/heihei999/huasheng-mcp"
The Agent will automatically complete all the download, installation, and configuration steps. You don't have to do anything.
Method 2: Install It Yourself
Step 1: Install
pip install xingce-solver[sse]If you don't have Python installed, go to https://www.python.org/downloads/ to download and install it, and check "Add Python to PATH".
Step 2: Start the Service
xingce-solver-mcp-sseWhen you see Uvicorn running on http://0.0.0.0:8000, the service has started successfully 👌
Step 3: Connect to the AI Assistant
For Claude Desktop users, add the following to the configuration file (%APPDATA%\Claude\claude_desktop_config.json):
{
"mcpServers": {
"行测解题": {
"type": "sse",
"url": "http://localhost:8000/sse"
}
}
}After saving, restart Claude Desktop, and you can directly call the civil service exam problem-solving tools in the chat!
ChatGPT / Other AI users: After starting the service, enter the address
http://localhost:8000/ssein any MCP SSE-compatible client.
Related MCP server: Sequential-Thinking
📖 Knowledge Base Overview
The knowledge base contains 442 method cards in total, covering the four major modules of the civil service exam:
Module | Number of Cards | Description |
📊 Data Analysis | 52 cards | Growth rates, proportions, multiples, averages, etc. |
🔢 Quantitative Relations | 118 cards | Work problems, travel problems, permutations and combinations, etc. |
🧠 Logical Reasoning | 148 cards | Figure reasoning, logical judgment, definition judgment, analogy reasoning |
💬 Verbal Comprehension | 95 cards | Main idea and intent, sentence expression, logical fill-in-the-blank |
🆕 Verbal Comprehension (New) | 18 cards | Sentence ordering, detail judgment, etc. |
🆕 Figure Reasoning (New) | 10 cards | Figure pattern special topics |
Total | 442 cards | Covers all core question types |
🛠️ Available Problem-Solving Tools (15 in total)
After connecting successfully, the AI assistant will automatically recognize the following tools:
Tool | What It Does |
| 📊 Solve data analysis questions |
| 🧠 Solve logical judgment questions |
| 🔍 Identify which module a question belongs to |
| 🔎 Search for problem-solving methods |
| 📇 View the detailed content of a method |
| 📋 View the source of a method |
| 🧭 Determine the question type and recommend a solution |
| 📝 Compose an analysis prompt |
| ✅ Generate a conservative answer prompt |
| 🎨 Figure reasoning method framework |
| 📌 Definition judgment method framework |
| 🔗 Analogy reasoning method framework |
| ⚖️ Analytical reasoning method framework |
| 🔢 Quantitative relations method framework |
| 💬 Verbal comprehension method framework |
🎯 Usage Examples in AI Assistants
All AI assistants that support MCP SSE can be connected (Claude Desktop, ChatGPT, Cherry Studio, etc.). Among them, Cherry Studio visualizes each tool call process, so beginners can intuitively see how the AI calls the knowledge base step by step to solve problems. It's especially suitable for those new to MCP.
Method 1: Send Text Questions Directly
After connecting, just type your question:
"Help me solve a data analysis question: In 2020, the revenue of a certain industry was 13.2 billion yuan, a year-over-year increase of 10%. What was the approximate revenue in 2019? A. 10 billion yuan B. 11 billion yuan C. 12 billion yuan D. 13.2 billion yuan"
The AI assistant will automatically call the tools and return the analysis process and answer.
Method 2: Send a Screenshot and Let the AI Read the Question (Highly Recommended)
Take a screenshot of a question from a practice app, PDF, or online course → send the screenshot directly to the AI assistant → the AI uses its "eyes" to read the image → automatically calls the problem-solving tools → instant answer
Any AI assistant that supports multimodal input can do this (Claude Desktop, ChatGPT, etc.). You don't need to type manually—just take a photo or screenshot. It's especially convenient for practicing on mobile or tablet.
Method 3: Search for Problem-Solving Methods
"Search for problem-solving methods about growth rate comparison"
The AI assistant will call the search_methods tool to find matching problem-solving techniques from the 442 method cards.
Method 4: Let the Agent Batch-Practice Questions
If you're using a coding agent like Claude Code or Codex, you can give it a path to process in batches:
"Read all the civil service exam question images in this folder, call the problem-solving tools one by one, and compile the answers into a table"
Great for intensive practice right before the exam.
📝 Battle-Tested Problem-Solving Prompt
A problem-solving SOP that the author has verified through real practice, which makes the AI strictly follow the "route → get scaffold → solve by rules" chain when calling MCP tools, preventing the AI from skipping the knowledge base and answering based on intuition. Copy the entire block below and send it to the AI assistant:
你是一个专业的公考行测名师。每次解答行测题目时,你必须严格遵循以下 SOP(标准操作流程) 链条来使用你的 MCP 知识库,绝不能跳过或卡死在任何一步:
【强制解题步骤】
第一步:提取与路由
当你收到用户的题目(或图片)时,你必须首先调用路由工具 route_xingce_question。
question_text 参数:仅填入你提取出来的纯净"行测题目原文"(如果有图片,必须提取图片中的完整题目文字,绝不能只填用户的闲聊!)。
module_hint 参数:如果用户指定了方法(如"十字交叉法"),必须填入此处;若无指定则留空。
第二步:获取脚手架
路由工具会返回一个结果,其中包含 recommended_tool(例如 get_quantity_relation_scaffold)。看清楚推荐的工具名后,你必须立刻去调用那个推荐的工具,从而获取详细的解题规则和公式!
注意:初次解答时禁止重复调用第一步的路由工具。但如果用户后续反驳、补充条件或提出新方法,允许你再次调用路由工具重新查阅资料!
第三步:按规则解答
拿到脚手架规则后,严格按照知识库给出的模板和步骤,结合用户指定的思路,为用户深度解答。
【异常兜底】
如果在第一步返回 "unknown" 或无匹配,或者在任何一步发生错误,只需尝试 1 次。如果依然失败,请立刻彻底放弃调用工具,直接动用你的内部推理能力为用户解答!⚙️ Advanced Settings
Changing the Port
The default port is 8000. If it's occupied, you can change it:
set MCP_PORT=8080
xingce-solver-mcp-sseLAN Sharing
To let other devices on the same LAN use it:
set MCP_HOST=0.0.0.0
xingce-solver-mcp-sseThen other devices connect to http://your-IP-address:8000/sse.
🧪 Test Status
✅ 661 tests passed, 35 skipped, with full coverage of all 442 method cards in the knowledge base.
📋 Version History
Version | Highlights |
v0.7.0 | Knowledge base expanded from 292 to 442 cards, added SSE server, beginner-friendly |
v0.6.0 | Figure reasoning framework, 8 anti-patterns |
v0.5.1 | Module context boundary hardening, verified with 330 real exam questions |
v0.5.0 | Manual override for module context |
v0.4.3 | Conservative routing hardening, 57/60 on a 60-question stress test |
v0.4.2 | Data material signal recognition |
v0.4.1 | Answer gating security hardening |
v0.4.0 | First MCP integration version |
💡 Questions? Submit them on GitHub Issues
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