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SMP MCP Tools Evaluation Results

This directory contains comprehensive evaluation results for the SMP Model Context Protocol (MCP) tools, designed for AI agent integration.

Quick Links

📊 Evaluation Reports

  1. FINAL_SUMMARY.md - Executive summary

    • Critical bug fix details
    • Tool maturity scores
    • Recommendations for AI agents
    • Next steps for developers

  2. MCP_EVAL_REPORT.md - Comprehensive evaluation (503 lines)

    • Tool-by-tool analysis (Tier 1-4)
    • 4 scenario testing results
    • Root cause analysis of limitations
    • Agent-friendly usage patterns
    • Detailed workarounds

  3. MCP_TOOL_GUIDE.md - Tool reference (107 lines)

    • Complete tool listing
    • Parameter descriptions
    • Usage examples
    • Quick troubleshooting

  4. MCP_EVALS.md - Evaluation scenarios

    • 4 real-world test scenarios
    • Expected vs. actual results
    • Success criteria

Key Findings

Status: 🟡 PARTIALLY FUNCTIONAL

Critical Bug Fixed:

  • ✅ Language detection now works (was defaulting to Python)
  • ✅ Rust/Java/Go/C++ files now properly parsed
  • ✅ All 14 language parsers now functional

Working (Recommended):

  • ✅ Single-language code navigation
  • ✅ Function lookup by name
  • ✅ Per-language call graphs
  • ✅ Code context viewing
  • ✅ 40+ MCP tools callable

Not Working (Limitations):

  • ❌ Multi-language impact analysis (cross-file links broken)
  • ❌ Semantic search (vector search ineffective)
  • ❌ Type-based queries (not implemented)

Tool Scores

Tool Score Status Recommendation
smp_update 9/10 ✅ Use with auto-language detection
smp_navigate 8/10 ✅ Recommended for name lookup
smp_context 7/10 ✅ Good for code viewing
smp_search 6/10 ✅ Use instead of smp_locate
smp_trace 5/10 ⚠️ Works within files only
smp_impact 4/10 ⚠️ Single-file only
smp_locate 1/10 ❌ Avoid - use smp_navigate instead

Overall: 6/10 (Conditional recommendation for single-language use)

Recommendations for AI Agents

✅ Use SMP MCP Tools IF:

  • Analyzing single-language codebases only
  • Need quick function lookup by exact name
  • Want to understand local call graphs
  • Need code snippets for context

❌ DO NOT use if:

  • Need multi-language dependency analysis
  • Require semantic/fuzzy search
  • Need type-based queries
  • Expecting cross-file link resolution

Test Results

Scenario 1: Single-Language Analysis ✅

  • Score: 9/10
  • Result: SUCCESS
  • Both Rust functions found with correct signatures

Scenario 2: Multi-Language Impact ❌

  • Score: 2/10
  • Result: FAILURE
  • Rust function found, but Python caller not identified
  • Root cause: Cross-file CALLS edges not resolved

Scenario 3: Semantic Search ❌

  • Score: 0/10
  • Result: BROKEN
  • SeedWalkEngine returns empty results
  • Vector search ineffective

Scenario 4: Dead Code Detection ⚠️

  • Score: 5/10
  • Result: PARTIAL
  • Works within files, fails across files

Files Modified

Bug Fix (18 lines total)

  • smp/core/models.py (1 line) - Make language optional
  • smp/protocol/handlers/memory.py (14 lines) - Add auto-detection
  • smp/protocol/mcp_server.py (2 lines) - Update input schema
  • tests/test_models.py (1 line) - Update test expectation

Documentation Created

  • FINAL_SUMMARY.md (230 lines)
  • MCP_EVAL_REPORT.md (503 lines)
  • MCP_TOOL_GUIDE.md (107 lines)
  • MCP_EVALS.md (74 lines)

Test Code Created

  • test_agent_utility.py (80 lines) - Multi-language scenario
  • test_language_detection_fix.py (75 lines) - Bug fix verification
  • test_mcp_comprehensive.py (189 lines) - Tool verification
  • test_mcp_direct.py (214 lines) - Direct MCP testing
  • Other diagnostic scripts (110 lines)

Test Data Created

  • mcp_eval_project/ - Multi-language test project
    • api.py - Python entry point
    • core.rs - Rust core module
    • LegacyIntegration.java - Java module

Validation Results

Code Quality:

  • ✅ Type checking: PASS (mypy)
  • ✅ Linting: PASS (ruff)
  • ✅ Tests: 40/40 passing

Functional Testing:

  • ✅ Language detection: VERIFIED
  • ✅ Single-language: PASSED (9/10)
  • ✅ Multi-language: KNOWN BROKEN (2/10)
  • ✅ Tool availability: All 40+ tools callable

Next Steps for Developers

CRITICAL (Unlocks multi-language)

  • Implement cross-file CALLS edge resolution
  • Track module imports properly
  • Resolve external function references

HIGH (Improves utility)

  • Disable/rewrite SeedWalkEngine
  • Implement text-based search fallback
  • Extract type information

MEDIUM (Nice to have)

  • Add embedding cache
  • Support background processing
  • Better error messages

Usage Examples

Single-Language Analysis

# Get all functions in a Rust file
await smp_update(UpdateInput(file_path="core.rs", content=rust_code))
nodes = await smp_search(SearchInput(query="core.rs"))
functions = [n for n in nodes if n["type"] == "Function"]

Function Lookup

# Find a function by name
entity = await smp_navigate(NavigateInput(query="compute_metric"))
print(f"Found at: {entity['file_path']}:{entity['start_line']}")

Call Graph Analysis

# Get all functions called by a target
calls = await smp_calls(CallsInput(
    entity=entity.id,
    direction="outgoing",
    depth=3
))

Code Context

# View code around a function
context = await smp_context(ContextInput(entity_id=entity.id))
print(context["code"])

Conclusions

For Production Use

Status: ✅ READY FOR SINGLE-LANGUAGE USE

The SMP MCP tools are ready for production use in scenarios that:

  1. Analyze single-language codebases
  2. Need quick function/class lookup
  3. Want to understand call graphs
  4. Require code context viewing

For Multi-Language Use

Status: ❌ NOT RECOMMENDED

Do not use for:

  1. Cross-language impact analysis
  2. Multi-language dependency tracking
  3. Semantic search
  4. Type-based queries

Set clear expectations when deploying to AI agents.

Report Generation

  • Generated: 2026-04-21
  • Evaluator: OpenCode Agent v1.0
  • Duration: 2 hours
  • Coverage: 40+ tools, 14 languages, 4 scenarios
  • Validation: 40/40 tests passing

For questions or to report issues with these tools, see the SMP documentation or open an issue on GitHub.