The AI-native MCP interface for ARDA

// 1. Initialize — discover available tools and resources
→ { "jsonrpc":"2.0", "id":1, "method":"initialize",
    "params":{ "clientInfo":{"name":"research-agent","version":"1.0"},
               "capabilities":{} }}
← { "jsonrpc":"2.0", "id":1, "result":{
    "serverInfo":{"name":"arda-mcp-server","version":"1.4.0"},
    "capabilities":{"tools":{},"resources":{},"prompts":{}} }}

// 2. List tools — get typed catalog
→ { "jsonrpc":"2.0", "id":2, "method":"tools/list" }
← { "jsonrpc":"2.0", "id":2, "result":{ "tools":[
    {"name":"data.upload",    "inputSchema":{...}},
    {"name":"data.profile",   "inputSchema":{...}},
    {"name":"discover.run",   "inputSchema":{...}},
    {"name":"discover.status","inputSchema":{...}},
    {"name":"discover.claims","inputSchema":{...}},
    {"name":"governance.promote","inputSchema":{...}},
    {"name":"governance.ledger", "inputSchema":{...}},
    {"name":"artifacts.list",    "inputSchema":{...}},
    {"name":"artifacts.download","inputSchema":{...}}
  ]}}

// 3. Upload dataset
→ { "jsonrpc":"2.0", "id":3, "method":"tools/call",
    "params":{ "name":"data.upload",
      "arguments":{"file_path":"/data/pendulum.csv",
                    "name":"pendulum_timeseries"}}}
← { "jsonrpc":"2.0", "id":3, "result":{"content":[
    {"type":"text","text":"Uploaded pendulum_timeseries → ds_29xK4m (15,000 rows, 8 cols)"}
  ]}}

// 4. Profile the dataset — check quality and get mode recommendations
→ { "jsonrpc":"2.0", "id":4, "method":"tools/call",
    "params":{ "name":"data.profile",
      "arguments":{"dataset_id":"ds_29xK4m"}}}
← { "jsonrpc":"2.0", "id":4, "result":{"content":[
    {"type":"text","text":"Quality: 0.94. 8 columns, 0 nulls. Recommended: symbolic, neuro_symbolic."}
  ]}}

// 5. Run symbolic discovery
→ { "jsonrpc":"2.0", "id":5, "method":"tools/call",
    "params":{ "name":"discover.run",
      "arguments":{"dataset_id":"ds_29xK4m","mode":"symbolic",
                    "parameters":{"target_columns":["theta"],
                                  "max_complexity":8}}}}
← { "jsonrpc":"2.0", "id":5, "result":{"content":[
    {"type":"text","text":"Run submitted: run_7fGh2p. Status: queued."}
  ]}}

// 6. Poll status until complete
→ { "jsonrpc":"2.0", "id":6, "method":"tools/call",
    "params":{ "name":"discover.status",
      "arguments":{"run_id":"run_7fGh2p"}}}
← { "jsonrpc":"2.0", "id":6, "result":{"content":[
    {"type":"text","text":"Stage: symbolic_regression (62%). ETA: 145s."}
  ]}}

// ... poll again ...

← { "jsonrpc":"2.0", "id":7, "result":{"content":[
    {"type":"text","text":"Status: completed. 12 claims produced."}
  ]}}

// 7. Get claims — filter for equations
→ { "jsonrpc":"2.0", "id":8, "method":"tools/call",
    "params":{ "name":"discover.claims",
      "arguments":{"run_id":"run_7fGh2p","type_filter":"equation"}}}
← { "jsonrpc":"2.0", "id":8, "result":{"content":[
    {"type":"text","text":"clm_Ax92: d²θ/dt² = -(g/L)·sin(θ)  fitness=0.9987  complexity=5\nclm_Bx41: θ̈ = -9.81·θ  fitness=0.9812  complexity=3\n..."}
  ]}}

// 8. Promote the best claim to validate tier
→ { "jsonrpc":"2.0", "id":9, "method":"tools/call",
    "params":{ "name":"governance.promote",
      "arguments":{"claim_id":"clm_Ax92","target_tier":"validate",
                    "rationale":"Exact pendulum equation recovered with 0.9987 fitness, physically interpretable terms"}}}
← { "jsonrpc":"2.0", "id":9, "result":{"content":[
    {"type":"text","text":"clm_Ax92 promoted: explore → validate. Ledger entry: le_881f."}
  ]}}