Claude-skill-registry-data mcp-server-evaluations
Evaluate MCP servers for quality and reliability. Verify tool functionality, test error handling, generate tests, and assess response quality with no dependencies other than curl. Use this when validating MCP server implementations, testing OpenAPI-to-MCP conversions, or assessing API tool quality.
git clone https://github.com/majiayu000/claude-skill-registry-data
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry-data "$T" && mkdir -p ~/.claude/skills && cp -r "$T/data/mcp-server-evaluations-skills" ~/.claude/skills/majiayu000-claude-skill-registry-data-mcp-server-evaluations && rm -rf "$T"
data/mcp-server-evaluations-skills/SKILL.mdMCP Server Evaluations Skill
Systematically evaluate MCP servers to ensure they function correctly, handle errors gracefully, and meet quality standards.
Workflow
Phase 1: Environment Verification
- Verify MCP server is running
curl -s http://localhost:3030/health # Expected: 200 OK curl -s -X POST http://localhost:3030/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","id":1,"method":"ping"}' # Expected: {"jsonrpc":"2.0","id":1,"result":{}}
Phase 2: Tool Discovery
-
List all available tools
curl -X POST http://localhost:3030/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","method":"tools/list","id":1}' -
Verify tool completeness
- All OpenAPI operations exposed as tools
- Tool names follow consistent convention (e.g.,
,getUsers
)createOrder - Descriptions are clear and actionable
- Required vs optional parameters clearly marked
- Parameter types match OpenAPI schema
-
Document discovered tools — Create inventory of tools for systematic testing.
Phase 3: Functional Testing
For each discovered tool:
-
Basic functionality test
curl -X POST http://localhost:3030/mcp \ -H "Content-Type: application/json" \ -d '{ "jsonrpc": "2.0", "method": "tools/call", "params": { "name": "<tool_name>", "arguments": { <valid_arguments> } }, "id": 2 }' -
Verify response structure
- Response contains expected data
- Data types match schema
- No unexpected null values
- Pagination works (if applicable)
-
Error handling test — Call with invalid/missing arguments:
curl -X POST http://localhost:3030/mcp \ -H "Content-Type: application/json" \ -d '{ "jsonrpc": "2.0", "method": "tools/call", "params": { "name": "<tool_name>", "arguments": {} }, "id": 3 }' -
Verify error response quality
- Error message is actionable
- Missing required parameters identified
- HTTP status codes propagated correctly
Phase 4: Question-Based Evaluation
Generate and test with realistic user questions:
-
Generate 10+ test questions covering:
- Simple single-tool queries
- Multi-step workflows requiring multiple tools
- Edge cases (empty results, large datasets)
- Error scenarios (invalid IDs, unauthorized access)
-
Execute each question through MCP client or Inspector
-
Score responses using evaluation criteria:
- Correctness: Does the answer match expected result?
- Completeness: Is all relevant information included?
- Clarity: Is the response well-structured?
- Performance: Response time within acceptable limits?
Phase 5: Quality Scoring
Calculate overall quality score:
| Category | Weight | Criteria |
|---|---|---|
| Tool Discovery | 20% | All operations exposed, proper naming |
| Basic Functionality | 30% | Valid inputs return correct responses |
| Error Handling | 20% | Graceful errors with actionable messages |
| Question Accuracy | 20% | Test questions answered correctly |
| Performance | 10% | Response times < 5s for standard ops |
Pass threshold: 80% overall score
Quick Evaluation Checklist
Run this minimal check for fast validation:
# 1. Health check curl -s http://localhost:3030/health | grep -q "" && echo "✓ Health OK" || echo "✗ Health FAILED" # 2. MCP ping curl -s -X POST http://localhost:3030/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","id":1,"method":"ping"}' | jq -e '.jsonrpc == "2.0" and .result' > /dev/null && echo "✓ Ping OK" || echo "✗ Ping FAILED" # 3. Tools list curl -s -X POST http://localhost:3030/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","method":"tools/list","id":1}' | jq '.result.tools | length' | xargs -I {} echo "✓ {} tools discovered" # 4. Sample tool call (adjust tool name and args) curl -s -X POST http://localhost:3030/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"listPets","arguments":{}},"id":2}' | jq '.result' > /dev/null && echo "✓ Tool call OK" || echo "✗ Tool call FAILED"
Test Question Templates
Use these patterns to generate effective test questions:
- List/Query: "Show me all [resources] that match [criteria]"
- Get Details: "What are the details of [resource] with ID [id]?"
- Create: "Create a new [resource] with [properties]"
- Update: "Update [resource] [id] to change [field] to [value]"
- Delete: "Remove [resource] with ID [id]"
- Aggregate: "How many [resources] exist with [status]?"
- Search: "Find [resources] where [field] contains [term]"
- Workflow: "Create a [resource], then update it, then list all"
References
For detailed documentation:
- references/mcp-inspector-guide.md — Inspector setup & usage
- references/evaluation-criteria.md — Quality metrics & scoring
- references/question-templates.md — Test question generation
Example: Petstore API Evaluation
# 1. Run health checks curl -s http://localhost:3030/health curl -s -X POST http://localhost:3030/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","id":1,"method":"ping"}' | jq -e '.jsonrpc == "2.0" and .result' > /dev/null && echo "✓ Ping OK" || echo "✗ Ping FAILED" # 2. Tool discovery curl -s -X POST http://localhost:3030/mcp \ -H "Content-Type: application/json" \ -d '{"jsonrpc":"2.0","method":"tools/list","id":1}' | jq '.result.tools' # 3. Test questions: # - "List all available pets" # - "Show details of pet with ID 1" # - "Find pets with status 'available'" # - "Create a new pet named 'Fluffy'"