MCP-Compliant Server Variant (Experimental)

[peterzan]

Overview

Implement an experimental ILETP server variant using Anthropic's Model Context Protocol (MCP) as the underlying communication standard. This is one of multiple possible implementation approaches for ILETP's headless server architecture and should be developed in parallel with protocol-agnostic variants.

Status: Experimental / Exploratory
Dependencies: Requires headless server architecture (Issue #1)
Priority: Medium (community-driven exploration)

Important Note: This issue is provided for community members who fork the repository and wish to build implementations. Any work completed here will not be merged back into this repository—it's intended for independent forks and derivative projects. That said, if you build something based on this issue, please let me know! I'd love to see what the community creates and may link to notable implementations.

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Context

ILETP's core specifications are intentionally protocol-agnostic, focusing on trust, consensus, and multi-agent coordination concepts rather than specific implementation protocols. MCP offers a standardized approach for AI-to-tool communication that could accelerate ILETP adoption within MCP-compatible ecosystems (Claude Desktop, IDEs, development tools).

This Issue explores MCP as ONE implementation path, not THE implementation path.

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Goals

1. Demonstrate ILETP concepts using MCP primitives - Show how ILETP's trust protocols, consensus mechanisms, and orchestration can be expressed using MCP's resource/tool/prompt model
2. Enable MCP ecosystem integration - Allow ILETP to work with existing MCP clients (Claude Desktop, IDE extensions, etc.)
3. Validate protocol compatibility - Test whether MCP's design supports ILETP's requirements (multi-model coordination, trust scoring, privacy preservation)
4. Provide implementation reference - Document how ILETP specifications map to MCP concepts for future implementers

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Technical Requirements

Core MCP Server Implementation

• MCP Server Initialization

  • Implement MCP server following MCP specification
  • Support stdio transport (required) and SSE transport (optional)
  • Proper capability negotiation with MCP clients
  • Server metadata and versioning

• ILETP Orchestration as MCP Tools

  • Expose ILETP Specification 1 (Orchestration Engine) as MCP tools:
    • iletp/orchestrate - Route query to multiple models with consensus
    • iletp/trust_score - Calculate trust score for given responses
    • iletp/synthesize - Combine multi-model outputs with provenance
  • Tool input/output schemas defined in JSON Schema
  • Error handling and validation per MCP spec

• ILETP Resources as MCP Resources

  • Expose conversation history as conversation://{id} resources
  • Expose trust scores as trust-score://{query-id} resources
  • Expose audit trails as audit://{session-id} resources
  • Support resource templates for dynamic access
  • Implement resource subscriptions for real-time updates

• Multi-Model Coordination via MCP

  • Coordinate calls to multiple LLM providers (Anthropic, OpenAI, Google, etc.)
  • Maintain separate MCP client connections to each provider (if they expose MCP servers)
  • Fallback to direct API calls for non-MCP providers
  • Handle concurrent model invocations with proper synchronization

ILETP-Specific Features

• Trust & Consensus Protocol (Spec 2)

  • Implement confidence-weighted consensus as MCP tool
  • Expose trust scores via MCP resources
  • Support real-time trust score updates via resource subscriptions
  • Return structured trust metadata (contributing models, confidence levels, dissent analysis)

• Dynamic Agent Orchestration (Spec 7)

  • Implement query complexity analysis
  • Dynamic model selection based on requirements
  • Diversity index calculation
  • Expose orchestration decisions via MCP resources for transparency

• Privacy-Preserving Orchestration (Spec 9)

  • Open Question: Can MCP support encrypted collaboration?
  • Investigate zero-knowledge proofs compatibility with MCP transport
  • Document limitations if privacy features cannot be fully implemented via MCP

• Session & Context Management (Spec 4, 5, 6)

  • Persistent conversation sessions
  • Context preservation across MCP client reconnections
  • Asynchronous task handling with status updates via resources
  • Cross-session context federation

Developer Experience

• Configuration & Setup

  • Simple installation via npm/pip/cargo (choose appropriate for implementation language)
  • Configuration file for API keys (stored securely, NOT in repo)
  • Support for multiple deployment modes (local, server, containerized)
  • Clear documentation on MCP client requirements

• Testing

  • Unit tests for MCP protocol compliance
  • Integration tests with real MCP clients (Claude Desktop, etc.)
  • Test coverage for ILETP trust protocols
  • Performance benchmarks for multi-model orchestration

• Documentation

  • Architecture overview (how ILETP specs map to MCP)
  • API reference for MCP tools/resources
  • Quickstart guide for MCP client users
  • Comparison with protocol-agnostic implementation (from Issue #1)
  • Known limitations and workarounds

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Acceptance Criteria

Minimum Viable MCP Server

• Server starts successfully and advertises ILETP capabilities to MCP clients
• At least 3 ILETP specifications implemented as MCP tools/resources:
  • Orchestration (Spec 1)
  • Trust & Consensus (Spec 2)
  • Dynamic Agent Orchestration (Spec 7)
• Successfully coordinates 2+ AI models (e.g., Claude + GPT-4)
• Returns trust scores with provenance in MCP-compliant format
• Works with at least one MCP client (Claude Desktop or compatible)

Quality Standards

• Code follows MCP best practices and conventions
• Comprehensive error handling (graceful degradation when models fail)
• Security: API keys never exposed in logs or responses
• Performance: Multi-model coordination completes within reasonable time (<30s for typical query)
• Documentation: README with setup, usage, and architecture explanation

Validation

• Demonstrate working integration with MCP-compatible client
• Compare trust scores between MCP variant and direct API implementation (should match)
• Show audit trail preservation through MCP resources
• Document any ILETP features that cannot be implemented via MCP

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Open Questions

These should be explored during implementation and documented in findings:

Protocol Compatibility

1. Privacy & Encryption: Can MCP's transport layer support ILETP Spec 9 (Privacy-Preserving Orchestration) requirements for zero-knowledge proofs and encrypted collaboration?

2. Trust Score Representation: How should ILETP's multi-dimensional trust scores (confidence, provenance, dissent) be represented in MCP's resource model? JSON structure? Separate resources?

3. Real-Time Updates: Should trust score updates during consensus calculation be streamed via MCP resource subscriptions, or returned atomically at completion?

4. Agent Independence (Spec 8): How do we monitor and preserve agent independence when operating through MCP abstraction layer? Does MCP's protocol expose enough information for diversity metrics?

Implementation Strategy

5. Language Choice: Should this be implemented in TypeScript/JavaScript (MCP reference implementation language), Python (common for AI projects), or Rust (performance + safety)?

6. MCP Client Compatibility: Which MCP clients should we prioritize for testing? Claude Desktop? Custom clients? IDE extensions?

7. Fallback Mechanisms: When an MCP client doesn't support a required feature (e.g., resource subscriptions), how should the server gracefully degrade?

8. State Management: Should the MCP server be stateless (client sends full context) or stateful (server maintains sessions)? MCP spec allows both.

Ecosystem Integration

9. Tool Discovery: How should ILETP tools be documented/discoverable within MCP ecosystems? Should we create a registry entry?

10. Interoperability: If multiple ILETP implementations exist (MCP variant, REST variant, GraphQL variant), how do we ensure consistent trust scores and behavior?

11. Provider Limitations: Not all LLM providers expose MCP servers. How do we handle hybrid scenarios (some models via MCP, others via direct API)?

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Non-Goals (Out of Scope)

This Issue does NOT aim to:

• ❌ Replace ILETP's protocol-agnostic specifications with MCP-specific requirements
• ❌ Make MCP the "official" or "recommended" implementation approach
• ❌ Deprecate or discourage non-MCP implementations
• ❌ Modify ILETP core specifications to favor MCP
• ❌ Build a production-ready server (this is experimental/reference)
• ❌ Implement all 10 ILETP specifications initially (start with core 3-4)

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Success Metrics

We'll consider this Issue successful if:

1. Proof of Concept: Working MCP server demonstrating ILETP trust protocols
2. Documentation: Clear comparison of MCP vs. protocol-agnostic approaches
3. Community Learning: Findings documented for future implementers
4. Ecosystem Test: Validated that ILETP concepts can be expressed via MCP
5. Decision Support: Provides data to help community choose implementation paths

Even if the MCP variant reveals limitations or challenges, documenting those findings is a success.

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Related Issues

• Issue #1: Headless Server Architecture (Foundation)
• Future: Issue #3 could explore GraphQL variant, gRPC variant, etc.

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Resources

• Model Context Protocol Specification
• MCP TypeScript SDK
• MCP Python SDK
• ILETP Specifications - Core protocol-agnostic requirements
• ILETP Use Cases - Context for implementation priorities

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Labels

experimental MCP protocol-integration help wanted good second issue architecture

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Call for Contributions

Interested in MCP? This is a great opportunity to:

• Learn MCP protocol by implementing a real use case
• Contribute to ILETP's ecosystem exploration
• Document findings that benefit the broader community

New to MCP? This Issue includes learning resources and clear acceptance criteria to guide implementation.

Questions? Comment below or join discussions in #general channel.

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Maintainer Note: This experimental variant will be evaluated alongside other implementation approaches (REST, GraphQL, etc.). Success is measured by learning and documentation quality, not adoption metrics. All implementation paths are equally valid for ILETP.

NOTE: Direction provided by me (Peter), documentation provided by Claude.