feat: MCP (Model Context Protocol) server

- POST /mcp (JSON-RPC 2.0): initialize, ping, tools/list, tools/call; notifications -> 202
- tools: cortiq_route (classify -> routing decision) and cortiq_chat (route -> answer)
- gated by protocols.mcp; admin meta marks it implemented
- docs: README/README.ru protocol tables, highlights and status updated for
  streaming, Anthropic, embeddings, semantic cache and MCP

CHANGELOG.md

@@ -23,6 +23,8 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/).
   semantically near a previous one (cosine threshold, TTL, ring buffer), skipping the
   model call. Partitioned by routing signature; hit-rate and cost saved are tracked and
   shown on the dashboard; configurable from Settings (`[cache]`).
+- **MCP server** (`POST /mcp`, JSON-RPC 2.0): exposes routing to MCP-native orchestrators
+  via two tools — `cortiq_route` (classify → decision) and `cortiq_chat` (route → answer).
 
 ## [0.1.0] - 2026-06-30
 

README.md

@@ -35,8 +35,10 @@ One OpenAI-compatible endpoint → automatic model selection from your pool
 
 ## ✨ Highlights
 
-- **Drop-in OpenAI API.** Point any OpenAI client at the gateway and send `model: "cortiq-auto"`.
+- **Drop-in OpenAI API + streaming.** Point any OpenAI client at the gateway and send `model: "cortiq-auto"`; `stream: true` is fully supported (SSE).
+- **Multi-protocol.** OpenAI Chat & Embeddings, **Anthropic Messages** (in/out, streaming), and an **MCP** server (`POST /mcp`) exposing routing as tools for agent orchestrators.
 - **Intelligent routing.** `complexity.tier` → ordered model pool (`low → local`, `high → cloud`), with fallback and graceful degradation when the router is down.
+- **Semantic cache.** Optional embedding-based cache returns a stored answer for prompts semantically near a previous one — skipping the model call (hit-rate & savings on the dashboard).
 - **Built-in multilingual admin console.** Manage models, routing, protocols, keys and secrets from a web UI — **no hand-editing TOML, no restart** (changes are hot-reloaded). Available in **7 languages** (en, ru, de, fr, es, zh, tr) with light/dark themes.
 - **Live analytics.** Per-request stats (tokens, cost, latency, success rate, failovers), time-series charts, breakdowns by model/tier/task, and a Prometheus `GET /metrics` endpoint.
 - **Playground.** Send a prompt through the live pipeline and inspect the routing decision.
@@ -147,12 +149,12 @@ Each adapter is toggled in the config — take only what you need.
 
 | Protocol | Endpoint | Status |
 |---|---|---|
-| OpenAI Chat Completions | `POST /v1/chat/completions` | ✅ implemented |
+| OpenAI Chat Completions | `POST /v1/chat/completions` | ✅ implemented (+ streaming) |
+| OpenAI Embeddings | `POST /v1/embeddings` | ✅ implemented |
+| Anthropic Messages | `POST /v1/messages` | ✅ implemented (+ streaming) |
+| MCP (Model Context Protocol) | `POST /mcp` (JSON-RPC) | ✅ implemented |
 | OpenAI Completions (legacy) | `POST /v1/completions` | planned |
-| OpenAI Embeddings | `POST /v1/embeddings` | planned |
 | OpenAI Models | `GET /v1/models` | planned |
-| Anthropic Messages | `POST /v1/messages` | planned |
-| MCP (Model Context Protocol) | JSON-RPC / SSE | planned |
 | Native passthrough | `POST /route` | planned |
 
 ## Supported providers (outbound)
@@ -160,7 +162,7 @@ Each adapter is toggled in the config — take only what you need.
 | Provider | Covers |
 |---|---|
 | `openai` (OpenAI-compatible) | OpenAI, OpenRouter, Together, Groq, **vLLM, llama.cpp server, LM Studio, Ollama (`/v1`)** |
-| `anthropic` | Claude Messages API (planned) |
+| `anthropic` | Claude Messages API (+ streaming) |
 | `ollama` | native Ollama API |
 | `http` | arbitrary HTTP endpoint (custom adapter) |
 
@@ -228,10 +230,12 @@ cargo test                 # config round-trip, routing validation
 
 ## Status
 
-🚧 Implemented so far: OpenAI Chat Completions, routing with fallback & graceful
-degradation, cost/token accounting, the **embedded multilingual admin console with
-hot config reload**, statistics and Prometheus `GET /metrics`. Planned: streaming
-(SSE), Anthropic provider/inbound, embeddings, MCP. See the roadmap in
+Implemented: OpenAI Chat Completions **with SSE streaming**, **Anthropic** provider +
+inbound `/v1/messages` (streaming), **embeddings**, a **semantic cache**, **MCP** server,
+routing with fallback & graceful degradation, cost/token accounting, the **embedded
+multilingual admin console with hot config reload**, statistics and Prometheus
+`GET /metrics`. Planned: OpenAI Completions/Models, native passthrough, per-account
+routing, feedback loop. See the roadmap in
 [docs/ARCHITECTURE.md](https://github.com/infosave2007/cortiq-gateway/blob/master/docs/ARCHITECTURE.md).
 Contributions welcome — see [CONTRIBUTING.md](https://github.com/infosave2007/cortiq-gateway/blob/master/CONTRIBUTING.md).
 

README.ru.md

@@ -141,12 +141,12 @@ print(resp.choices[0].message.content)
 
 | Протокол | Endpoint | Статус |
 |---|---|---|
-| OpenAI Chat Completions | `POST /v1/chat/completions` | ✅ реализовано |
+| OpenAI Chat Completions | `POST /v1/chat/completions` | ✅ реализовано (+ стриминг) |
+| OpenAI Embeddings | `POST /v1/embeddings` | ✅ реализовано |
+| Anthropic Messages | `POST /v1/messages` | ✅ реализовано (+ стриминг) |
+| MCP (Model Context Protocol) | `POST /mcp` (JSON-RPC) | ✅ реализовано |
 | OpenAI Completions (legacy) | `POST /v1/completions` | план |
-| OpenAI Embeddings | `POST /v1/embeddings` | план |
 | OpenAI Models | `GET /v1/models` | план |
-| Anthropic Messages | `POST /v1/messages` | план |
-| MCP (Model Context Protocol) | JSON-RPC / SSE | план |
 | Native passthrough | `POST /route` | план |
 
 ## Поддерживаемые провайдеры (исходящие)
@@ -154,7 +154,7 @@ print(resp.choices[0].message.content)
 | Провайдер | Покрывает |
 |---|---|
 | `openai` (OpenAI-совместимый) | OpenAI, OpenRouter, Together, Groq, **vLLM, llama.cpp server, LM Studio, Ollama (`/v1`)** |
-| `anthropic` | Claude Messages API (план) |
+| `anthropic` | Claude Messages API (+ стриминг) |
 | `ollama` | нативный Ollama API |
 | `http` | произвольный HTTP-эндпоинт (свой адаптер) |
 
@@ -179,10 +179,12 @@ cargo test                 # round-trip конфига, валидация ро
 
 ## Статус
 
-🚧 Уже работает: OpenAI Chat Completions, роутинг с fallback и мягкой деградацией,
-учёт стоимости/токенов, **встроенная многоязычная панель управления с горячей
-перезагрузкой конфига**, статистика и Prometheus `GET /metrics`. В планах: стриминг
-(SSE), провайдер/вход Anthropic, embeddings, MCP. Дорожная карта —
+Реализовано: OpenAI Chat Completions **со стримингом (SSE)**, провайдер и вход
+**Anthropic** `/v1/messages` (стриминг), **embeddings**, **семантический кэш**,
+**MCP**-сервер, роутинг с fallback и мягкой деградацией, учёт стоимости/токенов,
+**встроенная многоязычная панель управления с горячей перезагрузкой конфига**,
+статистика и Prometheus `GET /metrics`. В планах: OpenAI Completions/Models, native
+passthrough, per-account роутинг, feedback-loop. Дорожная карта —
 [docs/ARCHITECTURE.ru.md](docs/ARCHITECTURE.ru.md). Контрибьюции приветствуются —
 см. [CONTRIBUTING.ru.md](CONTRIBUTING.ru.md).
 

src/admin/mod.rs

@@ -281,7 +281,7 @@ async fn meta() -> ApiResult {
         "caps": ["tools", "vision"],
         "protocols_impl": {
             "openai_chat": true, "openai_completions": false, "openai_embeddings": true,
-            "openai_models": false, "anthropic_messages": true, "mcp": false, "native_passthrough": false
+            "openai_models": false, "anthropic_messages": true, "mcp": true, "native_passthrough": false
         },
         "languages": ["en", "ru", "de", "fr", "es", "zh", "tr"],
     }))

src/protocols/mcp.rs

@@ -0,0 +1,162 @@
+//! MCP (Model Context Protocol) server: `POST /mcp` (JSON-RPC 2.0).
+//!
+//! Exposes the gateway's routing to MCP-native orchestrators as two tools:
+//! `cortiq_route` (classify a prompt → routing decision) and `cortiq_chat`
+//! (run a prompt through intelligent routing → answer). Single JSON endpoint;
+//! notifications are accepted with `202`. Gated by `protocols.mcp`.
+
+use crate::model::{ChatRequest, GenParams, Message, RequestMeta, RoutingDirective};
+use crate::state::SharedState;
+use axum::response::{IntoResponse, Response};
+use axum::{extract::State, http::StatusCode, routing::post, Json, Router};
+use serde_json::{json, Value};
+
+pub fn routes() -> Router<SharedState> {
+    Router::new().route("/mcp", post(handler))
+}
+
+fn parse_routing(model: &str) -> RoutingDirective {
+    if let Some(rest) = model.strip_prefix("cortiq-auto") {
+        RoutingDirective::Auto {
+            profile: rest.strip_prefix(':').map(|p| p.to_string()),
+        }
+    } else {
+        RoutingDirective::Pinned {
+            model_id: model.to_string(),
+        }
+    }
+}
+
+fn tools_list() -> Value {
+    json!([
+        {
+            "name": "cortiq_route",
+            "description": "Classify a prompt and return the routing decision (task type, complexity tier, score, and the model the gateway would select).",
+            "inputSchema": {
+                "type": "object",
+                "properties": { "text": { "type": "string", "description": "The prompt to classify." } },
+                "required": ["text"]
+            }
+        },
+        {
+            "name": "cortiq_chat",
+            "description": "Run a prompt through the gateway's intelligent routing and return the selected model's answer.",
+            "inputSchema": {
+                "type": "object",
+                "properties": {
+                    "prompt": { "type": "string", "description": "The user prompt." },
+                    "model": { "type": "string", "description": "Optional: cortiq-auto[:profile] or a model id (default cortiq-auto)." }
+                },
+                "required": ["prompt"]
+            }
+        }
+    ])
+}
+
+fn tool_text(text: String, is_error: bool) -> Value {
+    json!({ "content": [{ "type": "text", "text": text }], "isError": is_error })
+}
+
+async fn handle_tool_call(
+    state: &SharedState,
+    params: &Value,
+) -> std::result::Result<Value, (i64, String)> {
+    let name = params["name"].as_str().unwrap_or("");
+    let args = &params["arguments"];
+    let live = state.live();
+    match name {
+        "cortiq_route" => {
+            let text = args["text"].as_str().unwrap_or("");
+            let prof = live.cfg.route.profile.clone();
+            match live.router.route(text, &prof).await {
+                Ok(Some(d)) => Ok(tool_text(
+                    format!(
+                        "task_label={}\ncomplexity_tier={}\ncomplexity_score={:.3}\ncandidates={:?}",
+                        d.task_label,
+                        d.complexity_tier,
+                        d.complexity_score,
+                        live.routing.candidates(&d.complexity_tier)
+                    ),
+                    false,
+                )),
+                _ => Ok(tool_text(
+                    "router unavailable — would use the default model".to_string(),
+                    false,
+                )),
+            }
+        }
+        "cortiq_chat" => {
+            let prompt = args["prompt"].as_str().unwrap_or("");
+            let model = args["model"].as_str().unwrap_or("cortiq-auto");
+            let req = ChatRequest {
+                routing: parse_routing(model),
+                messages: vec![Message {
+                    role: "user".into(),
+                    content: prompt.to_string(),
+                    tool_calls: vec![],
+                }],
+                tools: vec![],
+                params: GenParams::default(),
+                stream: false,
+                meta: RequestMeta {
+                    account: "mcp".into(),
+                    protocol: "mcp".into(),
+                    ..Default::default()
+                },
+            };
+            match state.pipeline.run(req, state).await {
+                Ok(resp) => {
+                    let answer = resp
+                        .choices
+                        .first()
+                        .map(|c| c.message.content.clone())
+                        .unwrap_or_default();
+                    Ok(tool_text(answer, false))
+                }
+                Err(e) => Ok(tool_text(e.to_string(), true)),
+            }
+        }
+        _ => Err((-32602, format!("unknown tool '{name}'"))),
+    }
+}
+
+async fn handler(State(state): State<SharedState>, Json(req): Json<Value>) -> Response {
+    if !state.live().cfg.protocols.mcp {
+        return (StatusCode::NOT_FOUND, "mcp protocol is disabled").into_response();
+    }
+
+    let method = req["method"].as_str().unwrap_or("").to_string();
+    let id = req.get("id").cloned();
+
+    // JSON-RPC notifications carry no id and expect no response
+    if id.is_none() || method.starts_with("notifications/") {
+        return StatusCode::ACCEPTED.into_response();
+    }
+    let id = id.unwrap_or(Value::Null);
+
+    let result: std::result::Result<Value, (i64, String)> = match method.as_str() {
+        "initialize" => {
+            let pv = req["params"]["protocolVersion"]
+                .as_str()
+                .unwrap_or("2024-11-05")
+                .to_string();
+            Ok(json!({
+                "protocolVersion": pv,
+                "capabilities": { "tools": {} },
+                "serverInfo": { "name": "cortiq-gateway", "version": env!("CARGO_PKG_VERSION") }
+            }))
+        }
+        "ping" => Ok(json!({})),
+        "tools/list" => Ok(json!({ "tools": tools_list() })),
+        "tools/call" => handle_tool_call(&state, &req["params"]).await,
+        other => Err((-32601, format!("method not found: {other}"))),
+    };
+
+    let body = match result {
+        Ok(r) => json!({ "jsonrpc": "2.0", "id": id, "result": r }),
+        Err((code, message)) => {
+            json!({ "jsonrpc": "2.0", "id": id, "error": { "code": code, "message": message } })
+        }
+    };
+    Json(body).into_response()
+}

src/protocols/mod.rs

@@ -2,6 +2,7 @@
 //! its protocol to/from the canonical model. Enabled via flags in `[protocols]`.
 
 pub mod anthropic_messages;
+pub mod mcp;
 pub mod openai_chat;
 pub mod openai_embeddings;
 
@@ -16,5 +17,6 @@ pub fn build_router() -> Router<SharedState> {
         .merge(openai_chat::routes())
         .merge(openai_embeddings::routes())
         .merge(anthropic_messages::routes())
-    // TODO: openai_completions, openai_models, mcp, native_passthrough.
+        .merge(mcp::routes())
+    // TODO: openai_completions, openai_models, native_passthrough.
 }