mirror of https://github.com/diegosouzapw/OmniRoute.git synced 2026-04-28 06:19:46 +00:00

diegosouzapw fa886231d3 docs(i18n): apply deep machine translation to 33 languages

2026-04-06 18:14:01 -03:00

28 KiB

Raw Blame History

OmniRoute A2A Server (Filipino)

🌐 Languages: 🇺🇸 English · 🇪🇸 es · 🇫🇷 fr · 🇩🇪 de · 🇮🇹 it · 🇷🇺 ru · 🇨🇳 zh-CN · 🇯🇵 ja · 🇰🇷 ko · 🇸🇦 ar · 🇮🇳 hi · 🇮🇳 in · 🇹🇭 th · 🇻🇳 vi · 🇮🇩 id · 🇲🇾 ms · 🇳🇱 nl · 🇵🇱 pl · 🇸🇪 sv · 🇳🇴 no · 🇩🇰 da · 🇫🇮 fi · 🇵🇹 pt · 🇷🇴 ro · 🇭🇺 hu · 🇧🇬 bg · 🇸🇰 sk · 🇺🇦 uk-UA · 🇮🇱 he · 🇵🇭 phi · 🇧🇷 pt-BR · 🇨🇿 cs · 🇹🇷 tr

Agent-to-Agent Protocol v0.3— Nagbibigay-daan sa sinumang ahente ng AI na gamitin ang OmniRoute bilang isang intelligent na ahente sa pagruruta sa pamamagitan ng JSON-RPC 2.0.

Inilalantad ng A2A Server ang OmniRoute bilang isangfirst-class agentna maaaring matuklasan ng ibang mga ahente, magtalaga ng mga gawain, at makipagtulungan sa paggamit ng A2A Protocol.---

Arkitektura

┌──────────────────────────────────────────────────────────────────┐
│                    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

Mabilis na Simula

Agent Discovery

Ang bawat A2A-compatible na ahente ay naglalantad ngAgent Cardsa /.well-known/agent.json:```bash curl http://localhost:20128/.well-known/agent.json


**Tugon:**```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` — Synchronous Execution

Magpadala ng mensahe sa isang kasanayan at tanggapin ang kumpletong tugon.```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"} } }'


**Tugon:**```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` — SSE Streaming

Kapareho ng mensahe/ipadala ngunit ibinabalik ang Mga Kaganapang Ipinadala ng Server para sa real-time na 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"}] } }'


**Mga Kaganapan sa SSE:**```
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`

Ang mga ruta ay nag-uudyok sa pamamagitan ng intelligent na pipeline ng OmniRoute na may ganap na pagmamasid.

Mga Parameter (sa metadata):

Parameter	Uri	Default	Paglalarawan
`modelo`	`string`	`"awto"`	Target na modelo (hal., `claude-sonnet-4`, `gpt-4o`, `auto`)
`combo`	`string`	aktibong combo	Tukoy na combo na dadaan sa
`badyet`	`numero`	wala	Pinakamataas na halaga sa USD para sa kahilingang ito
`gampanin`	`string`	wala	Pahiwatig ng tungkulin ng gawain: `coding`, `review`, `planning`, `analysis`, `debugging`, `documentation`

Pagbabalik:

Patlang	Paglalarawan
`artifacts[].content`	Ang teksto ng tugon ng LLM
`metadata.routing_explanation`	Nababasa ng tao na paliwanag ng desisyon sa pagruruta
`metadata.cost_envelope`	Tinantyang vs aktwal na gastos sa currency
`metadata.resilience_trace`	Array ng mga kaganapan (primary_selected, fallback_needed, atbp.)
`metadata.policy_verdict`	Kung pinayagan ang kahilingan at bakit	### `quota-management`

Sumasagot sa mga query sa natural na wika tungkol sa mga quota ng provider.

Mga uri ng query (hinuha mula sa nilalaman ng mensahe):

Pattern ng Query	Uri ng Tugon
Naglalaman ng `"ranggo"`, `"pinaka quota"`, `"pinakamahusay"`	Niraranggo ang mga provider ayon sa natitirang quota
Naglalaman ng `"libre"`, `"suggest"`	Naglilista ng mga libreng combo o nagmumungkahi ng mga free-tier na provider
Default	Buong buod ng quota na may mga babala para sa mga provider na mababa ang quota	---

Task Lifecycle

submitted ──→ working ──→ completed
                       ──→ failed
              ──────────→ cancelled

Estado	Paglalarawan
`naisumite`	Nagawa ang gawain, nakapila para sa pagpapatupad
`nagtatrabaho`	Ang handler ng kasanayan ay nagsasagawa ng
`nakumpleto`	Nagtagumpay ang pagpapatupad, magagamit ang mga artifact
`nabigo`	Nabigo ang pagpapatupad o nag-expire ang gawain (TTL: 5 min default)
`kinansela`	Kinansela ng kliyente sa pamamagitan ng `tasks/cancel`

Terminal states: completed, failed, cancelled (walang karagdagang transition)
Ang mga nag-expire na gawain sa isumite o gumagana ay awtomatikong minarkahan bilang bigo
Ang mga gawain ay kinokolekta ng basura pagkatapos ng 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

Ang isang ahente ng orkestra ay nagtatalaga ng pagbuo ng code sa OmniRoute, pagkatapos ay ipinapasa ang output sa isang ahente ng pagsusuri.```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}


### 💡 Use Case 2: Quota-Aware Agent Swarm

Maraming ahente ang nagbabahagi ng quota sa pamamagitan ng OmniRoute, gamit ang kakayahan sa quota para mag-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}] ⚠️ 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

Ang isang ahente sa pagsubaybay ay nag-stream ng mga tugon at nagpapakita ng pag-unlad sa 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(
        `\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

Para sa mga matagal nang gawain, i-poll ang status ng gawain sa halip na maghintay nang sabay-sabay.```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 — 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	pare-pareho	Ibig sabihin
-32700	—	Error sa pag-parse (di-wastong JSON)
-32600	`INVALID_REQUEST`	Di-wastong kahilingan sa JSON-RPC o hindi awtorisadong
-32601	`METHOD_NOT_FOUND`	Hindi alam na paraan o kasanayan
-32602	`INVALID_PARAMS`	Nawawala o di-wastong mga parameter
-32603	`INTERNAL_ERROR`	Nabigo ang pagpapatupad ng kasanayan
-32001	`GAWAIN_HINDI_NATAGPUAN`	Hindi nakita ang Task ID
-32002	`KUMPLETO_MAG-GAWAIN`	Hindi mabago ang isang nakumpletong gawain
-32003	`HINDI AUTHORIZED`	Di-wasto o nawawala ang API key
-32004	`BUDGET_EXCEEDED`	Ang kahilingan ay lumampas sa naka-configure na badyet
-32005	`PROVIDER_UNAVAILABLE`	Walang available na provider	---

Authentication

Lahat ng hiling na /a2a ay nangangailangan ng isang Bearer token sa pamamagitan ng header ng Authorization:``` Authorization: Bearer YOUR_OMNIROUTE_API_KEY


Kung walang API key na naka-configure sa server (ang `OMNIROUTE_API_KEY` ay walang laman), ang pagpapatotoo ay na-bypass.---

## 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

| Tampok | MCP Server | A2A Server |
| ----------------- | ---------------------------- | ------------------------------------------------- |
|**Protocol**| Model Context Protocol | Agent-to-Agent Protocol v0.3 |
|**Sasakyan**| stdio / HTTP | HTTP (JSON-RPC 2.0) |
|**Pagtuklas**| Listahan ng tool sa pamamagitan ng MCP | `/.well-known/agent.json` |
|**Granularity**| 16 indibidwal na tool | 2 mataas na antas ng kasanayan |
|**Pinakamahusay para sa**| Mga ahente ng IDE (Cursor, VS Code) | Multi-agent system (LangChain, CrewAI) |
|**Pag-stream**| Hindi suportado | SSE sa pamamagitan ng `mensahe/stream` |
|**Pagsubaybay sa gawain**| Hindi | Buong lifecycle (naisumite → nakumpleto) |
|**Pagmamasid**| Audit log sa bawat tool call | Sobre ng gastos + bakas ng katatagan + hatol ng patakaran |---

## Lisensya

Bahagi ng [OmniRoute](https://github.com/diegosouzapw/OmniRoute) — Lisensya ng MIT.

28 KiB Raw Blame History Unescape Escape