Files
OmniRoute/src/lib/a2a
Diego Rodrigues de Sa e Souza 590582711c fix(dashboard): orchestration canvas fase 3 — follow-ups da review final (#12639) (#12988)
* feat(api): hydrate memoryHits from the persisted history event

`GET /api/a2a/tasks/[id]` falls back to the persisted history row once a task
leaves the in-memory TTL window, and `reconstituteHistoricalTask` hard-coded
`metadata: {}` — so the drawer's "Memory used" section vanished for any
historical task, even though `executeA2ATaskWithState` had already written a
`memory_hits` event with the hits.

The fallback now reads that event: `data_json` is parsed and, when it yields at
least one well-formed hit, exposed as `metadata.memoryHits`. The event itself is
filtered out of `events` — it is observability, not a state transition, and
without the filter it leaked into the timeline as a duplicate of the row's
current state.

Reading is defensive throughout, mirroring `DrawerMemory`'s own validation: the
payload is caller-influenced and unvalidated end to end, so `JSON.parse` runs
inside `safeJsonParse`, non-arrays are rejected, and each entry must carry `id`,
`key`, `type` and `snippet` as strings (a non-string field would be rendered as
a React child and take the drawer down). Malformed input degrades to
`metadata: {}` and a 200 — never a 500.

Refs #12639

* fix(a2a): bound the memory recall with its own deadline

collectMemoryHits() runs BEFORE the skill handler and had no deadline at all,
so a slow memory backend delayed the start of every A2A task — the HTTP
genericBackend alone defaults to a 30s timeout.

The search now races a MEMORY_RECALL_TIMEOUT_MS (1500ms) deadline. Overshooting
degrades exactly like any other recall failure: empty hits, a warn log, and the
task proceeds normally (best-effort contract unchanged, nothing propagates).
The deadline timer is cleared in a finally on BOTH paths so no handle is left
holding the event loop open, and MemoryHitsDeps.timeoutMs makes it injectable
so the tests cost milliseconds instead of 1.5s of wall clock.

Refs #12639

* fix(dashboard): carry conductor requirements and focus the repeated task

The drawer's "Repeat" for a Conductor task dropped the runner/model pinning and
left the operator staring at the finished run:

- `hubTaskSchema` now parses the hub's `requirements` (`.catch(null)` so an odd
  shape never fails the whole task parse), and `ConductorTaskDetail` exposes
  `cli`/`model` (`null` when the hub sends none).
- `repeatReqForConductor` carries `cli`/`model` when present and OMITS them
  otherwise — the route's Zod takes both as optional strings, so a `null` would
  400. The two fields are independent.
- `performAction` reads the response body once and returns it, so the repeat can
  report the CANVAS id of the created task (`task_id` / `data.id` /
  `result.task.id`, each with its node prefix). `OrchestrationPageClient` then
  refetches and focuses it via `?node=`; History keeps its current behavior.
- `conductor-routes-auth.test.ts` covers the creation route through its `ROUTES`
  array; the duplicated source assertion left `conductor-create-route.test.ts`.

Refs #12639

* chore(a2a): follow-ups changelog

Changelog fragment for the five items PR-C delivers from #12639.

The sixth item on the issue — an authenticated panel path for A2A task
creation — stays deliberately out of scope and is recorded as such in a
comment on the issue rather than silently dropped: the JSON-RPC endpoint
accepts API keys only, and widening that endpoint's auth surface to serve a
UI convenience is the operator's call, not the implementation's.

Closes #12639
2026-09-10 10:23:52 -03:00
..
2026-06-30 06:54:29 -03:00

OmniRoute A2A Server

Agent-to-Agent Protocol v0.3 — Enables any AI agent to use OmniRoute as an intelligent routing agent via JSON-RPC 2.0.

The A2A Server exposes OmniRoute as a first-class agent that other agents can discover, delegate tasks to, and collaborate with using the A2A Protocol.


Architecture

┌──────────────────────────────────────────────────────────────────┐
│                    Orchestrator Agent                             │
│        (LangChain, CrewAI, AutoGen, Custom Agent)                │
└──────────────────────┬───────────────────────────────────────────┘
                       │  1. GET /.well-known/agent.json  (discover)
                       │  2. POST /a2a  (JSON-RPC 2.0)
                       ▼
┌──────────────────────────────────────────────────────────────────┐
│                     OmniRoute A2A Server                         │
│  ┌────────────────┐  ┌────────────────┐  ┌───────────────────┐  │
│  │  Task Manager  │  │  Skill Engine  │  │  SSE Streaming    │  │
│  │  (lifecycle)   │──│  (registry)    │──│  (real-time)      │  │
│  └────────────────┘  └────────┬───────┘  └───────────────────┘  │
│                               │                                  │
│  Skills:                      │                                  │
│    ├─ smart-routing ──────────┤  ┌────────────────────────────┐  │
│    └─ quota-management ───────┘  │  Routing Decision Logger   │  │
│                                  └────────────────────────────┘  │
└──────────────────────────────────────────────────────────────────┘
                       │
                       ▼  OmniRoute Gateway (internal)
              /v1/chat/completions, /api/combos, /api/usage/quota

Quick Start

Agent Discovery

Every A2A-compatible agent exposes an Agent Card at /.well-known/agent.json:

curl http://localhost:20128/.well-known/agent.json

Response:

{
  "name": "OmniRoute",
  "description": "Intelligent AI gateway with auto-routing across 50+ providers",
  "url": "http://localhost:20128/a2a",
  "version": "1.8.1",
  "capabilities": {
    "streaming": true,
    "pushNotifications": false
  },
  "skills": [
    {
      "id": "smart-routing",
      "name": "Smart Routing",
      "description": "Routes prompts through OmniRoute intelligent pipeline",
      "tags": ["routing", "llm", "multi-provider", "cost-optimization"],
      "examples": [
        "Write a hello world in Python",
        "Explain quantum computing using the cheapest provider"
      ]
    },
    {
      "id": "quota-management",
      "name": "Quota Management",
      "description": "Natural-language queries about provider quotas",
      "tags": ["quota", "analytics", "cost"],
      "examples": [
        "Which provider has the most quota remaining?",
        "Suggest a free combo for coding"
      ]
    }
  ],
  "authentication": {
    "schemes": ["bearer"],
    "apiKeyHeader": "Authorization"
  }
}

JSON-RPC 2.0 Methods

message/send — Synchronous Execution

Send a message to a skill and receive the complete response.

curl -X POST http://localhost:20128/a2a \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_KEY" \
  -d '{
    "jsonrpc": "2.0",
    "id": "1",
    "method": "message/send",
    "params": {
      "skill": "smart-routing",
      "messages": [{"role": "user", "content": "Write a Python hello world"}],
      "metadata": {"model": "auto", "combo": "fast-coding"}
    }
  }'

Response:

{
  "jsonrpc": "2.0",
  "id": "1",
  "result": {
    "task": { "id": "a1b2c3d4-...", "state": "completed" },
    "artifacts": [{ "type": "text", "content": "print('Hello, World!')" }],
    "metadata": {
      "routing_explanation": "Selected claude-sonnet via provider \"anthropic\" (latency: 1200ms, cost: $0.0030)",
      "cost_envelope": { "estimated": 0.005, "actual": 0.003, "currency": "USD" },
      "resilience_trace": [
        { "event": "primary_selected", "provider": "anthropic", "timestamp": "2026-03-04T..." }
      ],
      "policy_verdict": { "allowed": true, "reason": "within budget and quota limits" }
    }
  }
}

message/stream — SSE Streaming

Same as message/send but returns Server-Sent Events for real-time streaming.

curl -N -X POST http://localhost:20128/a2a \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_KEY" \
  -d '{
    "jsonrpc": "2.0",
    "id": "1",
    "method": "message/stream",
    "params": {
      "skill": "smart-routing",
      "messages": [{"role": "user", "content": "Explain quantum computing"}]
    }
  }'

SSE Events:

data: {"jsonrpc":"2.0","method":"message/stream","params":{"task":{"id":"...","state":"working"},"chunk":{"type":"text","content":"Quantum computing..."}}}

: heartbeat 2026-03-04T21:00:00Z

data: {"jsonrpc":"2.0","method":"message/stream","params":{"task":{"id":"...","state":"completed"},"metadata":{...}}}

tasks/get — Query Task Status

curl -X POST http://localhost:20128/a2a \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_KEY" \
  -d '{"jsonrpc":"2.0","id":"2","method":"tasks/get","params":{"taskId":"TASK_UUID"}}'

tasks/cancel — Cancel a Running Task

curl -X POST http://localhost:20128/a2a \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_KEY" \
  -d '{"jsonrpc":"2.0","id":"3","method":"tasks/cancel","params":{"taskId":"TASK_UUID"}}'

Skills Reference

smart-routing

Routes prompts through OmniRoute's intelligent pipeline with full observability.

Parameters (in metadata):

Parameter Type Default Description
model string "auto" Target model (e.g., claude-sonnet-4, gpt-4o, auto)
combo string active combo Specific combo to route through
budget number none Maximum cost in USD for this request
role string none Task role hint: coding, review, planning, analysis, debugging, documentation

Returns:

Field Description
artifacts[].content The LLM response text
metadata.routing_explanation Human-readable explanation of routing decision
metadata.cost_envelope Estimated vs actual cost with currency
metadata.resilience_trace Array of events (primary_selected, fallback_needed, etc.)
metadata.policy_verdict Whether the request was allowed and why

quota-management

Answers natural-language queries about provider quotas.

Query types (inferred from message content):

Query Pattern Response Type
Contains "ranking", "most quota", "best" Providers ranked by remaining quota
Contains "free", "suggest" Lists free combos or suggests free-tier providers
Default Full quota summary with warnings for low-quota providers

Task Lifecycle

submitted ──→ working ──→ completed
                       ──→ failed
              ──────────→ cancelled
State Description
submitted Task created, queued for execution
working Skill handler is executing
completed Execution succeeded, artifacts available
failed Execution failed or task expired (TTL: 5 min default)
cancelled Cancelled by client via tasks/cancel
  • Terminal states: completed, failed, cancelled (no further transitions)
  • Expired tasks in submitted or working are auto-marked as failed
  • Tasks are garbage-collected after 2× TTL

Client Examples

Python — Orchestrator Agent

"""
A2A Client — Python example.
Discovers OmniRoute agent, sends a task, and processes the result.
"""
import requests
import json

BASE_URL = "http://localhost:20128"
API_KEY = "your-api-key"
HEADERS = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}",
}

# 1. Discover agent capabilities
agent_card = requests.get(f"{BASE_URL}/.well-known/agent.json").json()
print(f"Agent: {agent_card['name']} v{agent_card['version']}")
print(f"Skills: {[s['id'] for s in agent_card['skills']]}")

# 2. Send a smart-routing task
response = requests.post(f"{BASE_URL}/a2a", headers=HEADERS, json={
    "jsonrpc": "2.0",
    "id": "task-1",
    "method": "message/send",
    "params": {
        "skill": "smart-routing",
        "messages": [{"role": "user", "content": "Write a Python quicksort implementation"}],
        "metadata": {
            "model": "auto",
            "combo": "fast-coding",
            "budget": 0.10,
        }
    }
})
result = response.json()["result"]
print(f"\n📝 Response: {result['artifacts'][0]['content'][:200]}...")
print(f"🔀 Routing: {result['metadata']['routing_explanation']}")
print(f"💰 Cost: ${result['metadata']['cost_envelope']['actual']}")
print(f"🛡️ Policy: {result['metadata']['policy_verdict']['reason']}")

# 3. Query quota status
quota_resp = requests.post(f"{BASE_URL}/a2a", headers=HEADERS, json={
    "jsonrpc": "2.0",
    "id": "task-2",
    "method": "message/send",
    "params": {
        "skill": "quota-management",
        "messages": [{"role": "user", "content": "Which provider has the most quota remaining?"}],
    }
})
quota_result = quota_resp.json()["result"]
print(f"\n📊 Quota: {quota_result['artifacts'][0]['content']}")

TypeScript — Multi-Agent Orchestrator

/**
 * A2A Client — TypeScript example.
 * Shows agent discovery, task delegation, and streaming.
 */

const BASE_URL = "http://localhost:20128";
const API_KEY = "your-api-key";

interface JsonRpcResponse<T = any> {
  jsonrpc: "2.0";
  id: string | number;
  result?: T;
  error?: { code: number; message: string };
}

async function a2aCall<T>(method: string, params: Record<string, any>): Promise<T> {
  const resp = await fetch(`${BASE_URL}/a2a`, {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
      Authorization: `Bearer ${API_KEY}`,
    },
    body: JSON.stringify({
      jsonrpc: "2.0",
      id: `${method}-${Date.now()}`,
      method,
      params,
    }),
  });
  const json: JsonRpcResponse<T> = await resp.json();
  if (json.error) throw new Error(`[${json.error.code}] ${json.error.message}`);
  return json.result!;
}

// ── Agent Discovery ──
const agentCard = await fetch(`${BASE_URL}/.well-known/agent.json`).then((r) => r.json());
console.log(`Connected to: ${agentCard.name} (${agentCard.skills.length} skills)`);

// ── Smart Routing: Send a coding task ──
const routingResult = await a2aCall("message/send", {
  skill: "smart-routing",
  messages: [{ role: "user", content: "Implement a Redis cache wrapper in TypeScript" }],
  metadata: { model: "claude-sonnet-4", role: "coding" },
});
console.log("Response:", routingResult.artifacts[0].content);
console.log("Provider:", routingResult.metadata.routing_explanation);

// ── Quota Management: Find free alternatives ──
const quotaResult = await a2aCall("message/send", {
  skill: "quota-management",
  messages: [{ role: "user", content: "Suggest free combos for documentation" }],
});
console.log("Free combos:", quotaResult.artifacts[0].content);

// ── Streaming: Real-time response ──
const streamResp = await fetch(`${BASE_URL}/a2a`, {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    Authorization: `Bearer ${API_KEY}`,
  },
  body: JSON.stringify({
    jsonrpc: "2.0",
    id: "stream-1",
    method: "message/stream",
    params: {
      skill: "smart-routing",
      messages: [{ role: "user", content: "Explain microservices architecture" }],
    },
  }),
});

const reader = streamResp.body!.getReader();
const decoder = new TextDecoder();
while (true) {
  const { done, value } = await reader.read();
  if (done) break;
  const chunk = decoder.decode(value);
  for (const line of chunk.split("\n")) {
    if (line.startsWith("data: ")) {
      const event = JSON.parse(line.slice(6));
      if (event.params.chunk) {
        process.stdout.write(event.params.chunk.content);
      }
      if (event.params.task.state === "completed") {
        console.log("\n✅ Stream completed");
      }
    }
  }
}

Python — LangChain A2A Integration

"""
LangChain integration — Use OmniRoute A2A as a custom LLM.
"""
from langchain.llms.base import BaseLLM
from langchain.schema import LLMResult, Generation
import requests
from typing import List, Optional

class OmniRouteA2A(BaseLLM):
    base_url: str = "http://localhost:20128"
    api_key: str = ""
    model: str = "auto"
    combo: Optional[str] = None

    @property
    def _llm_type(self) -> str:
        return "omniroute-a2a"

    def _call(self, prompt: str, stop: Optional[List[str]] = None, **kwargs) -> str:
        response = requests.post(
            f"{self.base_url}/a2a",
            headers={
                "Content-Type": "application/json",
                "Authorization": f"Bearer {self.api_key}",
            },
            json={
                "jsonrpc": "2.0",
                "id": "langchain-1",
                "method": "message/send",
                "params": {
                    "skill": "smart-routing",
                    "messages": [{"role": "user", "content": prompt}],
                    "metadata": {
                        "model": self.model,
                        **({"combo": self.combo} if self.combo else {}),
                    },
                },
            },
        )
        result = response.json()["result"]
        return result["artifacts"][0]["content"]

    def _generate(self, prompts: List[str], stop=None, **kwargs) -> LLMResult:
        return LLMResult(
            generations=[[Generation(text=self._call(p, stop))] for p in prompts]
        )

# Usage
llm = OmniRouteA2A(
    base_url="http://localhost:20128",
    api_key="your-key",
    model="auto",
    combo="fast-coding",
)
result = llm("Write a Python function to merge two sorted lists")
print(result)

Go — A2A Client

package main

import (
	"bytes"
	"encoding/json"
	"fmt"
	"io"
	"net/http"
)

const baseURL = "http://localhost:20128"
const apiKey = "your-api-key"

type JsonRpcRequest struct {
	Jsonrpc string      `json:"jsonrpc"`
	ID      string      `json:"id"`
	Method  string      `json:"method"`
	Params  interface{} `json:"params"`
}

type JsonRpcResponse struct {
	Jsonrpc string      `json:"jsonrpc"`
	ID      string      `json:"id"`
	Result  interface{} `json:"result"`
	Error   *struct {
		Code    int    `json:"code"`
		Message string `json:"message"`
	} `json:"error"`
}

func a2aCall(method string, params interface{}) (*JsonRpcResponse, error) {
	body, _ := json.Marshal(JsonRpcRequest{
		Jsonrpc: "2.0",
		ID:      "go-1",
		Method:  method,
		Params:  params,
	})

	req, _ := http.NewRequest("POST", baseURL+"/a2a", bytes.NewReader(body))
	req.Header.Set("Content-Type", "application/json")
	req.Header.Set("Authorization", "Bearer "+apiKey)

	resp, err := http.DefaultClient.Do(req)
	if err != nil {
		return nil, err
	}
	defer resp.Body.Close()
	data, _ := io.ReadAll(resp.Body)

	var result JsonRpcResponse
	json.Unmarshal(data, &result)
	return &result, nil
}

func main() {
	// Discover agent
	resp, _ := http.Get(baseURL + "/.well-known/agent.json")
	defer resp.Body.Close()
	body, _ := io.ReadAll(resp.Body)
	fmt.Println("Agent Card:", string(body))

	// Send smart-routing task
	result, _ := a2aCall("message/send", map[string]interface{}{
		"skill":    "smart-routing",
		"messages": []map[string]string{{"role": "user", "content": "Hello from Go!"}},
		"metadata": map[string]interface{}{"model": "auto"},
	})
	out, _ := json.MarshalIndent(result.Result, "", "  ")
	fmt.Println("Result:", string(out))
}

Use Cases

🤖 Use Case 1: Multi-Agent Coding Pipeline

An orchestrator agent delegates code generation to OmniRoute, then passes the output to a review agent.

def coding_pipeline(task: str):
    # Step 1: Generate code via OmniRoute A2A
    code_result = a2a_send("smart-routing", [
        {"role": "user", "content": f"Write production-quality code: {task}"}
    ], metadata={"model": "auto", "role": "coding"})
    code = code_result["artifacts"][0]["content"]

    # Step 2: Review the code via OmniRoute A2A (different model)
    review_result = a2a_send("smart-routing", [
        {"role": "user", "content": f"Review this code for bugs and improvements:\n\n{code}"}
    ], metadata={"model": "auto", "role": "review"})
    review = review_result["artifacts"][0]["content"]

    # Step 3: Check costs
    print(f"Code cost: ${code_result['metadata']['cost_envelope']['actual']}")
    print(f"Review cost: ${review_result['metadata']['cost_envelope']['actual']}")

    return {"code": code, "review": review}

💡 Use Case 2: Quota-Aware Agent Swarm

Multiple agents share quota through OmniRoute, using the quota skill to coordinate.

async def quota_aware_agent(agent_name: str, task: str):
    # Check quota before starting
    quota = a2a_send("quota-management", [
        {"role": "user", "content": "Which provider has the most quota remaining?"}
    ])
    print(f"[{agent_name}] {quota['artifacts'][0]['content']}")

    # Send request with budget constraint
    result = a2a_send("smart-routing", [
        {"role": "user", "content": task}
    ], metadata={"budget": 0.05})

    policy = result["metadata"]["policy_verdict"]
    if not policy["allowed"]:
        print(f"[{agent_name}] ⚠️ Budget exceeded: {policy['reason']}")
        # Fall back to free combo
        quota = a2a_send("quota-management", [
            {"role": "user", "content": "Suggest free combos"}
        ])
        print(f"[{agent_name}] Free alternatives: {quota['artifacts'][0]['content']}")

    return result

📊 Use Case 3: Real-Time Streaming Dashboard

A monitoring agent streams responses and displays progress in real-time.

async function streamingDashboard(prompt: string) {
  const response = await fetch(`${BASE_URL}/a2a`, {
    method: "POST",
    headers: { "Content-Type": "application/json", Authorization: `Bearer ${API_KEY}` },
    body: JSON.stringify({
      jsonrpc: "2.0",
      id: "dash-1",
      method: "message/stream",
      params: { skill: "smart-routing", messages: [{ role: "user", content: prompt }] },
    }),
  });

  let totalChunks = 0;
  const reader = response.body!.getReader();
  const decoder = new TextDecoder();

  while (true) {
    const { done, value } = await reader.read();
    if (done) break;

    for (const line of decoder.decode(value).split("\n")) {
      if (line.startsWith("data: ")) {
        const event = JSON.parse(line.slice(6));
        const state = event.params.task.state;

        if (state === "working" && event.params.chunk) {
          totalChunks++;
          process.stdout.write(
            `\r[Chunk ${totalChunks}] ${event.params.chunk.content.slice(0, 50)}...`
          );
        }
        if (state === "completed") {
          const meta = event.params.metadata;
          console.log(
            `\n✅ Done | Cost: $${meta?.cost_envelope?.actual || 0} | Route: ${meta?.routing_explanation || "N/A"}`
          );
        }
        if (state === "failed") {
          console.error(`\n❌ Failed: ${event.params.metadata?.error}`);
        }
      }
    }
  }
}

🔁 Use Case 4: Task Polling Pattern

For long-running tasks, poll the task status instead of waiting synchronously.

import time

def poll_task(task_id: str, timeout: int = 60):
    """Poll task status until completion or timeout."""
    start = time.time()
    while time.time() - start < timeout:
        result = requests.post(f"{BASE_URL}/a2a", headers=HEADERS, json={
            "jsonrpc": "2.0",
            "id": "poll-1",
            "method": "tasks/get",
            "params": {"taskId": task_id},
        }).json()

        task = result["result"]["task"]
        state = task["state"]
        print(f"  Task {task_id[:8]}... state={state}")

        if state in ("completed", "failed", "cancelled"):
            return task
        time.sleep(2)

    # Timeout — cancel the task
    requests.post(f"{BASE_URL}/a2a", headers=HEADERS, json={
        "jsonrpc": "2.0",
        "id": "cancel-1",
        "method": "tasks/cancel",
        "params": {"taskId": task_id},
    })
    raise TimeoutError(f"Task {task_id} timed out after {timeout}s")

Error Codes

Code Constant Meaning
-32700 Parse error (invalid JSON)
-32600 INVALID_REQUEST Invalid JSON-RPC request or unauthorized
-32601 METHOD_NOT_FOUND Unknown method or skill
-32602 INVALID_PARAMS Missing or invalid parameters
-32603 INTERNAL_ERROR Skill execution failed
-32001 TASK_NOT_FOUND Task ID not found
-32002 TASK_ALREADY_COMPLETED Cannot modify a completed task
-32003 UNAUTHORIZED Invalid or missing API key
-32004 BUDGET_EXCEEDED Request exceeds configured budget
-32005 PROVIDER_UNAVAILABLE No available providers

Authentication

All /a2a requests require a Bearer token via the Authorization header:

Authorization: Bearer YOUR_OMNIROUTE_API_KEY

If no API key is configured on the server (OMNIROUTE_API_KEY is empty), authentication is bypassed.


File Structure

src/lib/a2a/
├── taskManager.ts         # Task lifecycle (create/update/cancel/list), TTL, cleanup
├── taskExecution.ts       # Generic task executor with state management
├── streaming.ts           # SSE stream formatting, heartbeat, chunk/completion events
├── routingLogger.ts       # Routing decision logger (stats, history, retention)
└── skills/
    ├── smartRouting.ts    # Smart routing skill (routes via /v1/chat/completions)
    └── quotaManagement.ts # Quota management skill (natural-language quota queries)

src/app/a2a/
└── route.ts               # Next.js API route handler (JSON-RPC 2.0 dispatch)

open-sse/mcp-server/
└── schemas/a2a.ts         # Zod schemas (AgentCard, Task, JSON-RPC, SSE events)

Comparison: MCP vs A2A

Feature MCP Server A2A Server
Protocol Model Context Protocol Agent-to-Agent Protocol v0.3
Transport stdio / HTTP HTTP (JSON-RPC 2.0)
Discovery Tool listing via MCP /.well-known/agent.json
Granularity 16 individual tools 2 high-level skills
Best for IDE agents (Cursor, VS Code) Multi-agent systems (LangChain, CrewAI)
Streaming Not supported SSE via message/stream
Task tracking No Full lifecycle (submitted → completed)
Observability Audit log per tool call Cost envelope + resilience trace + policy verdict

License

Part of OmniRoute — MIT License.