SWI-Prolog▌
by vpursuit
Access SWI-Prolog for secure logic programming, ladder logic, and PLC coding. Ideal for education, puzzles, and AI logic
Provides secure access to SWI-Prolog logic programming through dual query modes with sandboxed execution, dynamic knowledge base management, and mathematical operations for educational use cases, logic puzzle solving, and AI reasoning workflows.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Educational logic programming courses
- / Solving logic puzzles and constraints
- / AI reasoning workflow development
- / Interactive Prolog development
capabilities
- / Load and manage Prolog files
- / Add and remove facts and rules dynamically
- / Execute Prolog queries with deterministic pagination
- / Run queries with true backtracking engine mode
- / List Prolog symbols and predicates
- / Perform mathematical operations in Prolog
what it does
Provides secure access to SWI-Prolog logic programming environment through an MCP server with sandboxed execution and dynamic knowledge base management.
about
SWI-Prolog is a community-built MCP server published by vpursuit that provides AI assistants with tools and capabilities via the Model Context Protocol. Access SWI-Prolog for secure logic programming, ladder logic, and PLC coding. Ideal for education, puzzles, and AI logic It is categorized under ai ml, developer tools.
how to install
You can install SWI-Prolog in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
BSD-3-Clause
SWI-Prolog is released under the BSD-3-Clause license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
MCP Ecosystem by vpursuit
This monorepo contains Model Context Protocol (MCP) packages and products that enable AI assistants to work with SWI-Prolog, filesystems, and extensible plugin systems.
Products
SWI-Prolog MCP Server
Full-featured MCP server with Prolog knowledge base integration
A MCP server that lets tools-enabled LLMs work directly with SWI‑Prolog. It supports loading Prolog files, adding/removing facts and rules, listing symbols, and running queries with two modes: deterministic pagination and true engine backtracking.
- NPM:
@vpursuit/swipl-mcp-server - Documentation: products/swipl-mcp-server
- Quick Start:
npx @vpursuit/swipl-mcp-server
Features:
- Knowledge base management (load, assert, retract, dump)
- Two query modes: standard (
call_nth/2) and engine (true backtracking) - Expert Prolog assistance prompts (e.g. solving logic puzzles)
- Comprehensive security sandboxing
- Dynamic filesystem roots
- Plugin-based architecture
Architecture
This repository follows a products/plugins architecture:
- Products (
products/): Published packages that end-users install (e.g.,@vpursuit/swipl-mcp-server) - Plugins (
plugins/): Internal, reusable components bundled within products (not published separately)
Internal Plugin System
The MCP server is built with a modular plugin architecture. These plugins are internal dependencies bundled into the main product:
| Plugin | Description | Location |
|---|---|---|
@vpursuit/mcp-server-core | Plugin system foundation | plugins/server/core |
@vpursuit/mcp-server-prolog | SWI-Prolog integration | plugins/server/prolog |
@vpursuit/mcp-server-roots | Filesystem roots discovery | plugins/server/roots |
Note: These plugins are marked as private in their package.json and are bundled into @vpursuit/swipl-mcp-server. They are not published separately to npm.
Plugin System for Developers
If you're developing within this monorepo, you can use the plugin system directly:
import { McpServer } from '@modelcontextprotocol/sdk/server/mcp.js';
import { loadPlugins } from '@vpursuit/mcp-server-core';
import { plugin as prologPlugin } from '@vpursuit/mcp-server-prolog';
import { plugin as rootsPlugin } from '@vpursuit/mcp-server-roots';
const server = new McpServer({
name: 'my-mcp-server',
version: '1.0.0',
});
// Load plugins
await loadPlugins(server, [prologPlugin, rootsPlugin]);
📂 Repository Structure
This is a monorepo managed with npm workspaces. Each package can be developed, tested, and published independently.
model-context-lab/
├── products/
│ └── swipl-mcp-server/ # Main MCP server (published to npm)
├── plugins/
│ └── server/
│ ├── core/ # Plugin system foundation (internal)
│ ├── prolog/ # SWI-Prolog integration (internal)
│ └── roots/ # Filesystem roots discovery (internal)
├── docs/ # Monorepo-level documentation
├── .archive/ # Historical strategy documents
└── package.json # Workspace configuration
Each package has:
- Own
package.jsonwith independent versioning - Own
README.mdwith complete documentation - Own
LICENSE(BSD-3-Clause) - Own test suite
🔧 Development
Prerequisites
- Node.js ≥ 20.0.0
- SWI-Prolog (for testing Prolog integration)
- npm ≥ 9.0.0
Setup
# Clone repository
git clone https://github.com/vpursuit/model-context-lab.git
cd model-context-lab
# Install all dependencies
npm install
# Build all packages
npm run build
# Run all tests
npm test
Working with Packages
# Build specific package
npm run build -w plugins/server/core
# Test specific package
npm test -w plugins/server/prolog
# Clean all build artifacts
npm run clean
Package Development
Each package supports:
npm run build- TypeScript compilationnpm run clean- Remove build artifactsnpm test- Run Vitest testsnpm run test:watch- Watch mode for tests
Documentation
Product Documentation (swipl-mcp-server)
- Installation & Setup — Complete setup for all MCP clients
- Configuration — Filesystem roots, environment variables
- Troubleshooting — Common issues and debug mode
- Features Reference — Detailed prompts, resources, and tools documentation
- Examples — Copy-paste usage examples
- Architecture — Components, modes, and wire protocol
- Lifecycle — Server lifecycle, state, and persistence patterns
- Deployment — Release, packaging, and install from source
Monorepo Documentation
- Publishing Guide — How to publish packages to npm
- Contributing — Development workflow and guidelines
- Security — Security policies and vulnerability reporting
Contributing
We welcome contributions! Please see CONTRIBUTING.md for:
- Code of conduct
- Development workflow
- Testing requirements
- Pull request process
- Coding standards
For security issues, see SECURITY.md.
Publishing
Only products are published to npm under the @vpursuit scope:
- Products (e.g.,
@vpursuit/swipl-mcp-server) are published to npm for end users - Plugins are internal dependencies bundled within products (not published separately)
- Releases use semantic versioning:
v<version>(e.g.,v3.0.0) - Automated publishing via GitHub Actions
- Supply chain security: All packages published with npm provenance attestation
- See PUBLISHING.md for complete details
Security
All packages implement security best practices:
- File path restrictions
- Dangerous predicate blocking
- Pre-execution validation
- Timeout protection
- Module isolation
Supply Chain Security:
- Published with npm provenance attestation for build transparency
- OIDC-based publishing (no long-lived tokens)
- Cryptographically signed packages via Sigstore
See SECURITY.md for complete security documentation and reporting.
📄 License
All packages in this monorepo are licensed under BSD-3-Clause.
See LICENSE file for details.
🔗 Links
- GitHub: vpursuit/model-context-lab
- NPM Organization: @vpursuit
- Model Context Protocol: modelcontextprotocol.io
- SWI-Prolog: swi-prolog.org
Getting Started
For end users: Install the complete MCP server
npx @vpursuit/swipl-mcp-server
For monorepo developers: Work with the plugin system
git clone https://github.com/vpursuit/model-context-lab.git
cd model-context-lab
npm install
npm run build
For contributors: Set up the development environment
git clone https://github.com/vpursuit/model-context-lab.git
cd model-context-lab
npm install
npm run build
npm test
Questions? Open an issue or see our documentation.
FAQ
- What is the SWI-Prolog MCP server?
- SWI-Prolog is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for SWI-Prolog?
- This profile displays 34 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.6★★★★★34 reviews- ★★★★★Diya Srinivasan· Dec 28, 2024
Strong directory entry: SWI-Prolog surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Diya White· Dec 24, 2024
Useful MCP listing: SWI-Prolog is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Layla Okafor· Dec 16, 2024
SWI-Prolog has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Piyush G· Dec 12, 2024
Strong directory entry: SWI-Prolog surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Ira Dixit· Nov 19, 2024
SWI-Prolog is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Yusuf Desai· Nov 7, 2024
SWI-Prolog is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Dhruvi Jain· Nov 3, 2024
SWI-Prolog is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Yuki Liu· Oct 26, 2024
We wired SWI-Prolog into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Rahul Santra· Oct 22, 2024
We evaluated SWI-Prolog against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Hiroshi Dixit· Oct 10, 2024
We evaluated SWI-Prolog against two servers with overlapping tools; this profile had the clearer scope statement.
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