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> **Agent-to-Agent Protocol v0.3** β 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](https://google.github.io/A2A/).
---
## Architecture
```
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β Orchestrator Agent β
β (LangChain, CrewAI, AutoGen, Custom Agent) β
ββββββββββββββββββββββββ¬ββββββββββββββββββββββββββββββββββββββββββββ
β 1. GET /.well-known/agent.json (discover)
β 2. POST /a2a (JSON-RPC 2.0)
βΌ
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β OmniRoute A2A Server β
β ββββββββββββββββββ ββββββββββββββββββ βββββββββββββββββββββ β
β β Task Manager β β Skill Engine β β SSE Streaming β β
β β (lifecycle) ββββ (registry) ββββ (real-time) β β
β ββββββββββββββββββ ββββββββββ¬ββββββββ βββββββββββββββββββββ β
β β β
β Skills: β β
β ββ smart-routing βββββββββββ€ ββββββββββββββββββββββββββββββ β
β ββ quota-management ββββββββ β Routing Decision Logger β β
β ββββββββββββββββββββββββββββββ β
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β
βΌ 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`:
```bash
curl http://localhost:20128/.well-known/agent.json
```
**Response:**
```json
{
"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` β Synchronous Execution
Send a message to a skill and receive the complete response.
```bash
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:**
```json
{
"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` β SSE Streaming
Same as `message/send` but returns Server-Sent Events for real-time streaming.
```bash
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` β Query Task Status
```bash
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` β Cancel a Running Task
```bash
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 βββ working βββ completed
βββ failed
βββββββββββ 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 2Γ TTL
---
## Client Examples
### Python β Orchestrator Agent
```python
"""
A2A Client β 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"\nπ Response: {result['artifacts'][0]['content'][:200]}...")
print(f"π Routing: {result['metadata']['routing_explanation']}")
print(f"π° Cost: ${result['metadata']['cost_envelope']['actual']}")
print(f"π‘οΈ Policy: {result['metadata']['policy_verdict']['reason']}")
# 3. Query quota status
quota_resp = requests.post(f"{BASE_URL}/a2a", headers=HEADERS, json={
"jsonrpc": "2.0",
"id": "task-2",
"method": "message/send",
"params": {
"skill": "quota-management",
"messages": [{"role": "user", "content": "Which provider has the most quota remaining?"}],
}
})
quota_result = quota_resp.json()["result"]
print(f"\nπ Quota: {quota_result['artifacts'][0]['content']}")
```
### TypeScript β Multi-Agent Orchestrator
```typescript
/**
* A2A Client β TypeScript example.
* Shows agent discovery, task delegation, and streaming.
*/
const BASE_URL = "http://localhost:20128";
const API_KEY = "your-api-key";
interface JsonRpcResponse<T = any> {
jsonrpc: "2.0";
id: string | number;
result?: T;
error?: { code: number; message: string };
}
async function a2aCall<T>(method: string, params: Record<string, any>): Promise<T> {
const resp = await fetch(`${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}] ${json.error.message}`);
return json.result!;
}
// ββ Agent Discovery ββ
const agentCard = await fetch(`${BASE_URL}/.well-known/agent.json`).then((r) => r.json());
console.log(`Connected to: ${agentCard.name} (${agentCard.skills.length} skills)`);
// ββ Smart Routing: Send a coding task ββ
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);
// ββ Quota Management: Find free alternatives ββ
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);
// ββ Streaming: Real-time response ββ
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("\nβ
Stream completed");
}
}
}
}
```
### Python β LangChain A2A Integration
```python
"""
LangChain integration β 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 β A2A Client
```go
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
### π€ Use Case 1: Multi-Agent Coding Pipeline
An orchestrator agent delegates code generation to OmniRoute, then passes the output to a review agent.
```python
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: ${review_result['metadata']['cost_envelope']['actual']}")
return {"code": code, "review": review}
```
### π‘ Use Case 2: Quota-Aware Agent Swarm
Multiple agents share quota through OmniRoute, using the quota skill to coordinate.
```python
async def quota_aware_agent(agent_name: str, task: str):
# Check quota before starting
quota = a2a_send("quota-management", [
{"role": "user", "content": "Which provider has the most quota remaining?"}
])
print(f"[{agent_name}] {quota['artifacts'][0]['content']}")
# Send request with budget constraint
result = a2a_send("smart-routing", [
{"role": "user", "content": task}
], metadata={"budget": 0.05})
policy = result["metadata"]["policy_verdict"]
if not policy["allowed"]:
print(f"[{agent_name}] β οΈ Budget exceeded: {policy['reason']}")
# Fall back to free combo
quota = a2a_send("quota-management", [
{"role": "user", "content": "Suggest free combos"}
])
print(f"[{agent_name}] Free alternatives: {quota['artifacts'][0]['content']}")
return result
```
### π Use Case 3: Real-Time Streaming Dashboard
A monitoring agent streams responses and displays progress in real-time.
```typescript
async function streamingDashboard(prompt: string) {
const response = await fetch(`${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(
`\nβ
Done | Cost: $${meta?.cost_envelope?.actual || 0} | Route: ${meta?.routing_explanation || "N/A"}`
);
}
if (state === "failed") {
console.error(`\nβ Failed: ${event.params.metadata?.error}`);
}
}
}
}
}
```
### π Use Case 4: Task Polling Pattern
For long-running tasks, poll the task status instead of waiting synchronously.
```python
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 β 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 | β | 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/
βββ taskManager.ts # Task lifecycle (create/update/cancel/list), TTL, cleanup
βββ taskExecution.ts # Generic task executor with state management
βββ streaming.ts # SSE stream formatting, heartbeat, chunk/completion events
βββ routingLogger.ts # Routing decision logger (stats, history, retention)
βββ skills/
βββ smartRouting.ts # Smart routing skill (routes via /v1/chat/completions)
βββ quotaManagement.ts # Quota management skill (natural-language quota queries)
src/app/a2a/
βββ route.ts # Next.js API route handler (JSON-RPC 2.0 dispatch)
open-sse/mcp-server/
βββ 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 β completed) |
| **Observability** | Audit log per tool call | Cost envelope + resilience trace + policy verdict |
---
## License
Part of [OmniRoute](https://github.com/diegosouzapw/OmniRoute) β MIT License.
|