feat(agent): implement local Canvas Agent with MCP integration and HTTP server

canvas-agent/src/mcp-server.ts

@@ -0,0 +1,29 @@
+import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
+import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
+
+import { AGENT_PROMPT, loadConfig, type CanvasAgentConfig, VERSION } from "./config.js";
+import { toolDescriptions, toolInputSchemas, toolNames, type ToolName } from "./schemas.js";
+
+type CanvasAgentToolResponse = { ok?: boolean; result?: unknown; error?: string };
+
+export async function startMcpServer() {
+    const config = loadConfig(true);
+    const server = new McpServer({ name: "canvas-agent", version: VERSION }, { instructions: AGENT_PROMPT });
+    toolNames.forEach((name) => registerCanvasTool(server, config, name));
+    await server.connect(new StdioServerTransport());
+}
+
+function registerCanvasTool(server: McpServer, config: CanvasAgentConfig, name: ToolName) {
+    const schema = toolInputSchemas[name];
+    server.registerTool(name, { description: toolDescriptions[name], inputSchema: schema.shape }, async (input: unknown) => {
+        const result = await postCanvasAgentTool(config, name, schema.parse(input));
+        return { content: [{ type: "text" as const, text: JSON.stringify(result, null, 2) }] };
+    });
+}
+
+async function postCanvasAgentTool(config: CanvasAgentConfig, name: ToolName, input: unknown) {
+    const res = await fetch(`${config.url}/api/tools`, { method: "POST", headers: { "content-type": "application/json", "x-canvas-agent-token": config.token }, body: JSON.stringify({ name, input }) });
+    const body = (await res.json()) as CanvasAgentToolResponse;
+    if (!body.ok) throw new Error(body.error || "tool call failed");
+    return body.result;
+}