Prolog Mcp
What is Prolog Mcp
Prolog-MCP is a neurosymbolic AI server that integrates Prolog’s symbolic reasoning capabilities with the Model Context Protocol (MCP) to facilitate hybrid AI applications.
Use cases
Use cases for Prolog-MCP include developing intelligent agents, creating rule-based systems, performing advanced data analysis, and building applications that require dynamic knowledge updates.
How to use
To use Prolog-MCP, clone the repository from GitHub, install the necessary dependencies using npm, and build the project. You can then run the server and utilize its core tools for loading programs, executing queries, and managing sessions.
Key features
Key features include a persistent Prolog session for maintaining state, session management for saving and loading knowledge bases, four core tools for program loading and query execution, type safety through Zod schema validation, and a WebAssembly runtime for Trealla Prolog.
Where to use
Prolog-MCP can be used in fields such as artificial intelligence, natural language processing, knowledge representation, and any domain requiring complex logical reasoning.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Prolog Mcp
Prolog-MCP is a neurosymbolic AI server that integrates Prolog’s symbolic reasoning capabilities with the Model Context Protocol (MCP) to facilitate hybrid AI applications.
Use cases
Use cases for Prolog-MCP include developing intelligent agents, creating rule-based systems, performing advanced data analysis, and building applications that require dynamic knowledge updates.
How to use
To use Prolog-MCP, clone the repository from GitHub, install the necessary dependencies using npm, and build the project. You can then run the server and utilize its core tools for loading programs, executing queries, and managing sessions.
Key features
Key features include a persistent Prolog session for maintaining state, session management for saving and loading knowledge bases, four core tools for program loading and query execution, type safety through Zod schema validation, and a WebAssembly runtime for Trealla Prolog.
Where to use
Prolog-MCP can be used in fields such as artificial intelligence, natural language processing, knowledge representation, and any domain requiring complex logical reasoning.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
Prolog-MCP Server
A neurosymbolic AI server combining Prolog’s symbolic reasoning with Model Context Protocol (MCP) for hybrid AI applications.
Features:
- Persistent Prolog session: maintain state between tool calls
- Session management: save/load knowledge bases to disk
- Four core tools:
loadProgram: Load Prolog predicates/rulesrunPrologQuery: Execute complex logical queriessaveSession: Persist session stateloadSession: Restore previous sessions
- Type safety via Zod schema validation for all I/O
- WebAssembly runtime: Trealla Prolog in WASI environment
Integration with Cline/Roo/Copilot:
{ "mcpServers": { "prolog-mcp": { "command": "node", "args": [ "prolog-mcp/dist/index.js" ], "disabled": false, "alwaysAllow": [ "loadProgram", "runPrologQuery", "saveSession", "loadSession" ], "timeout": 15 } } }
Development:
git clone https://github.com/adamrybinski/prolog-mcp cd prolog-mcp npm install npm run build
Performance:
| Operation | Avg. Latency | Memory Usage |
|---|---|---|
| Query Execution | 12ms | 18MB |
| Session Save | 45ms | 22MB |
| Program Load | 8ms | 15MB |
Acknowledgements:
Built with Trealla Prolog and MCP Protocol
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
