PromptSmith

Reasoning as a Service - A Capability-Level 0 MCP Server that provides intelligent reasoning framework selection and meta-prompt generation for AI agents.

Purpose

PromptSmith analyzes tasks, determines their complexity and category, and generates optimized "meta-prompts" using the most appropriate reasoning framework.

Features

• 🧠 40 Reasoning Frameworks: Chain of Thought, Tree of Thoughts, ReAct, Reflexion, Graph of Thoughts, Program of Thoughts, and more
• 📊 Intelligent Task Analysis: Automatic category detection (code, math, logic, creative, research, data, planning) and complexity scoring (0–10)
• 🎯 Framework Selection: Heuristic-based selection of the optimal reasoning strategy
• 💾 Persistence: SQLite storage for reasoning traces and analytics
• 📈 Usage Statistics: Track framework usage and effectiveness

Installation

git clone https://github.com/your-org/promptsmith
cd promptsmith
uv sync

MCP Tools

Tool	Description
recommend_strategy	Analyze a task and recommend the optimal reasoning framework
generate_meta_prompt	Generate an optimized meta-prompt for a task
log_execution_feedback	Record feedback about prompt effectiveness
list_available_frameworks	List all available reasoning frameworks
get_usage_stats	Get usage statistics and analytics

Usage

As MCP Server

Add to your MCP client configuration (e.g. .mcp.json in your project root):

{
  "mcpServers": {
    "promptsmith": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/promptsmith", "python", "-m", "promptsmith.main"],
      "env": {
        "PYTHONPATH": "/path/to/promptsmith/src",
        "UV_LINK_MODE": "copy",
        "FASTMCP_SHOW_STARTUP_BANNER": "false"
      }
    }
  }
}

Programmatic Usage

from promptsmith.domain import FrameworkSelector, PromptBuilder

# Analyze a task
selector = FrameworkSelector()
analysis = selector.analyze("Write a recursive function to calculate fibonacci numbers")

print(f"Category: {analysis.category}")               # code
print(f"Complexity: {analysis.complexity_score}")     # ~3.3
print(f"Framework: {analysis.recommended_framework}") # program_of_thoughts

# Generate a meta-prompt
builder = PromptBuilder()
result = builder.build(analysis.task, analysis=analysis)
print(result.meta_prompt)

Reasoning Frameworks

40 frameworks across 8 categories, selected automatically based on task type and complexity.

Framework	Best For	Complexity Threshold
Role Prompting	Creative, General, Research	1.0
Emotion Prompting	Creative, General	1.0
Rephrase and Respond	General, Research	2.0
Chain of Thought	Math, Logic, Code	2.0
System 2 Attention	Logic, Research, General	3.0
Thread of Thought	Research, Data, General	3.0
Tab-CoT	Data, Math, Logic	3.0
Directional Stimulus	Creative, General	3.0
Skeleton of Thought	Creative, General, Planning	3.0
Self-Calibration	Math, Logic, General	3.0
Chain of Density	Research, Data, General	3.0
Prompt Paraphrasing	General, Logic	3.0
Sim-to-M	Logic, General	4.0
Self-Ask	Research, Logic, General	4.0
Step Back	Research, Logic, General	4.0
Analogical	General, Creative, Code	4.0
Program of Thoughts	Math, Code, Data	4.0
Plan and Solve	Planning, Code, Math	4.0
Self-Consistency	Math, Logic	4.0
Self-Refine	Creative, Code, General	4.0
Chain of Table	Data	4.0
Least to Most	Code, Math, Planning	5.0
Contrastive CoT	Math, Logic, Code	5.0
Active Prompting	General, Research, Logic	5.0
Faithful CoT	Math, Logic, Code	5.0
Demonstration Ensembling	General, Data, Logic	5.0
Maieutic	Research, Logic, General	5.0
Chain of Verification	Research, General, Data	5.0
Reverse CoT	Math, Logic, Code	5.0
Buffer of Thoughts	General, Math, Code	5.0
Complexity-Based	Math, Logic	6.0
Tree of Thoughts	Creative, Planning, Research	6.0
Mixture of Reasoning	General, Research, Logic	6.0
Meta-CoT	Logic, Math, Research	6.0
Cumulative Reasoning	Logic, Math, Research	6.0
Recursion of Thought	Math, Code, Logic	7.0
ReAct	Research, Code, Data	7.0
Reflexion	Code, Math, Logic	8.0
Graph of Thoughts	Planning, Research, Logic	8.0
Reasoning via Planning	Planning, Logic, Code	8.0

Architecture

src/promptsmith/
├── main.py              # MCP Server entry point
├── domain/
│   ├── frameworks.py    # 40 reasoning framework implementations
│   ├── selector.py      # Task analysis and framework selection
│   └── builder.py       # Meta-prompt assembly
├── persistence/
│   ├── models.py        # SQLAlchemy/Pydantic models
│   └── storage.py       # SQLite operations
└── utils/
    └── complexity.py    # Text complexity analysis

Integration with Other Agents

PromptSmith is designed to be called by other MCP-enabled agents.

result = mcp_call("promptsmith", "generate_meta_prompt", {
    "task": user_query,
    "context": relevant_context,
})
enhanced_response = llm.generate(result["meta_prompt"])

License

MIT