OpenEnded Philosophy MCP Server with NARS Integration
A sophisticated philosophical reasoning system that combines OpenEnded Philosophy with Non-Axiomatic Reasoning System (NARS) for enhanced epistemic analysis, truth maintenance, and multi-perspective synthesis.
Core Integration: Philosophy + NARS
This server uniquely integrates:
- NARS/ONA: Non-axiomatic reasoning with truth maintenance and belief revision
- Philosophical Pluralism: Multi-perspective analysis without privileging any single view
- Epistemic Humility: Built-in uncertainty quantification and revision conditions
- Coherence Dynamics: Emergent conceptual landscapes with stability analysis
Theoretical Foundation
Core Philosophical Architecture:
- Epistemic Humility: Every insight carries inherent uncertainty metrics
- Contextual Semantics: Meaning emerges through language games and forms of life
- Dynamic Pluralism: Multiple interpretive schemas coexist without hierarchical privileging
- Pragmatic Orientation: Efficacy measured through problem-solving capability
Computational Framework
1. Emergent Coherence Dynamics
C(t) = Σ_{regions} (R_i(t) × Stability_i) + Perturbation_Response(t)
Where:
C(t)
: Coherence landscape at time tR_i(t)
: Regional coherence patternsStability_i
: Local stability coefficientsPerturbation_Response(t)
: Adaptive response to new experiences
2. Fallibilistic Inference Engine
P(insight|evidence) = Confidence × (1 - Uncertainty_Propagation)
Key Components:
- Evidence limitation assessment
- Context dependence calculation
- Unknown unknown estimation
- Revision trigger identification
Quiick Start
{
"mcpServers": {
"openended-philosophy": {
"command": "uv",
"args": [
"--directory",
"/path/to/openended-philosophy-mcp",
"run",
"openended-philosophy-server"
],
"env": {
"PYTHONPATH": "/path/to/openended-philosophy-mcp",
"LOG_LEVEL": "INFO"
}
}
}
}
System Architecture
┌─────────────────────────────────────────┐
│ OpenEnded Philosophy Server │
├─────────────────────────────────────────┤
│ ┌─────────────┐ ┌─────────────────┐ │
│ │ Coherence │ │ Language │ │
│ │ Landscape │ │ Games │ │
│ └──────┬──────┘ └────────┬────────┘ │
│ │ │ │
│ ┌──────▼──────────────────▼────────┐ │
│ │ Dynamic Pluralism Framework │ │
│ └──────────────┬───────────────────┘ │
│ │ │
│ ┌──────────────▼───────────────────┐ │
│ │ Fallibilistic Inference Core │ │
│ └──────────────────────────────────┘ │
└─────────────────────────────────────────┘
NARS Integration Features
Non-Axiomatic Logic (NAL)
- Truth Values: (frequency, confidence) pairs for nuanced belief representation
- Evidence-Based Reasoning: Beliefs strengthen with converging evidence
- Temporal Reasoning: Handle time-dependent truths and belief projection
- Inference Rules: Deduction, induction, abduction, analogy, and revision
Enhanced Capabilities
- Truth Maintenance: Automatic belief revision when contradictions arise
- Memory System: Semantic embeddings + NARS attention buffer
- Reasoning Patterns: Multiple inference types for comprehensive analysis
- Uncertainty Tracking: Epistemic uncertainty propagation through inference chains
Installation
Clone the repository:
git clone https://github.com/angrysky56/openended-philosophy-mcp cd openended-philosophy-mcp
Install dependencies with uv:
uv sync
This will install all required Python packages, including
ona
(OpenNARS for Applications).
### For Direct Usage (without MCP client)
If you want to run the philosophy server directly using uv:
#### Prerequisites
1. Install uv if you haven't already:
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
- Restart your shell or run:
source $HOME/.cargo/env
Installation
Clone this repository:
git clone https://github.com/angrysky56/openended-philosophy-mcp cd openended-philosophy-mcp
Install dependencies with uv:
uv sync
Running the Server
Activate the virtual environment:
source .venv/bin/activate
Run the MCP server:
python -m openended_philosophy.server
The server will start and listen for MCP protocol messages on stdin/stdout. You can interact with it programmatically or integrate it with other MCP-compatible tools.
Available Tools
ask_philosophical_question
: Ask deep philosophical questions and receive thoughtful responsesexplore_philosophical_topic
: Explore philosophical topics in depth with guided discussion
Usage via MCP
Available Tools
1. analyze_concept
Analyzes a concept through multiple interpretive lenses without claiming ontological priority.
{
"concept": "consciousness",
"context": "neuroscience",
"confidence_threshold": 0.7
}
2. explore_coherence
Maps provisional coherence patterns in conceptual space.
{
"domain": "ethics",
"depth": 3,
"allow_revision": true
}
3. contextualize_meaning
Derives contextual semantics through language game analysis.
{
"expression": "truth",
"language_game": "scientific_discourse",
"form_of_life": "research_community"
}
4. generate_insights
Produces fallibilistic insights with built-in uncertainty quantification.
{
"phenomenon": "quantum_consciousness",
"perspectives": ["physics", "philosophy_of_mind", "information_theory"],
"openness_coefficient": 0.9
}
Philosophical Methodology
Wittgensteinian Therapeutic Approach
- Dissolve Rather Than Solve: Recognizes category mistakes
- Language Game Awareness: Context-dependent semantics
- Family Resemblance: Non-essentialist categorization
Pragmatist Orientation
- Instrumental Truth: Measured by problem-solving efficacy
- Fallibilism: All knowledge provisional
- Pluralism: Multiple valid perspectives
Information-Theoretic Substrate
- Pattern Recognition: Without ontological commitment
- Emergence: Novel properties from interactions
- Complexity: Irreducible to simple principles
Development Philosophy
This server embodies its own philosophical commitments:
- Open Source: Knowledge emerges through community
- Iterative Development: Understanding grows through use
- Bug-as-Feature: Errors provide learning opportunities
- Fork-Friendly: Multiple development paths encouraged
NARS Configuration & Setup
Installation Support
The server now exclusively supports pip
-installed ONA (OpenNARS for Applications).
uv add ona
Configuration via Environment Variables
Create a .env
file from the template:
cp .env.example .env
Key configuration options:
NARS_MEMORY_SIZE
: Concept memory size (default: 1000)NARS_INFERENCE_STEPS
: Inference depth (default: 50)NARS_SILENT_MODE
: Suppress ONA output (default: true)NARS_DECISION_THRESHOLD
: Decision confidence threshold (default: 0.6)
Testing NARS Integration
Verify your installation:
uv run python tests/test_nars_integration.py
Process Management
The improved NARS manager includes:
- Robust cleanup patterns preventing process leaks
- Signal handling for graceful shutdown (SIGTERM, SIGINT)
- Automatic recovery from subprocess failures
- Cross-platform support (Linux, macOS, Windows)
Troubleshooting
See docs/NARS_INSTALLATION.md
for detailed troubleshooting guide.
Contributing
We welcome contributions that:
- Enhance epistemic humility features
- Add new interpretive schemas
- Improve contextual understanding
- Challenge existing assumptions
- Strengthen NARS integration capabilities
License
MIT License - In the spirit of open-ended inquiry
Project Status: Towards Functional AI Philosophical Reasoning
This project is a highly promising research platform or advanced prototype for AI philosophical reasoning. It lays a strong architectural and conceptual groundwork for computational philosophy.
Strengths & Progress:
- Robust NARS Integration: The
NARSManager
provides a reliable interface to the NARS engine, crucial for non-axiomatic reasoning. - Modular Design: Clear separation of concerns (e.g.,
core
,nars
,llm_semantic_processor
) enhances maintainability and extensibility. - Conceptual Graphing (
networkx
): Effective use ofnetworkx
for representing coherence landscapes and conceptual relationships provides structured, machine-readable data for AI processing. - Philosophically Informed Prompts: The
LLMSemanticProcessor
demonstrates a good understanding of philosophical concepts in its prompt crafting.
Current Limitations & Path to "Functional and Useful":
To evolve into a truly "functional and useful tool" for independent, deep, and novel philosophical reasoning, the following areas require significant development:
- Depth of NLP: Current semantic similarity metrics are simplistic. Achieving nuanced philosophical reasoning demands more advanced NLP (e.g., contextual embeddings, fine-tuned models) to understand subtle semantic differences.
- Transparency of Synthesis: While
FallibilisticInference
performs complex synthesis, the AI needs to understand how insights are synthesized to truly reason philosophically, rather than just receiving a result. This implies making the synthesis process more transparent and controllable by the AI. - Explicit AI Interaction with Graphs: The AI needs explicit tools or APIs to actively query, manipulate, and reason over the
networkx
graphs, moving beyond them being merely data structures. - Emergent Philosophical Insight: The ultimate goal is for the AI to generate novel philosophical insights or arguments that extend beyond its programmed rules or NARS's current capabilities. This is the most challenging aspect and represents the frontier of this project.