feat(mcp): adding bypass of summarizer for mcp

packages/agents/sample.config.toml

@@ -0,0 +1,28 @@
+[API_KEYS]
+OPENAI = ""
+GROQ = ""
+ANTHROPIC = ""
+DEEPSEEK = ""
+GEMINI = ""
+
+[API_ENDPOINTS]
+OLLAMA = ""
+
+[VECTOR_DB]
+POSTGRES_USER="cairocoder"
+POSTGRES_PASSWORD="cairocoder"
+POSTGRES_ROOT_DB="cairocoder"
+POSTGRES_HOST="localhost"
+POSTGRES_PORT="5432"
+
+[GENERAL]
+PORT = 3_001
+SIMILARITY_MEASURE = "cosine"
+
+[HOSTED_MODE]
+DEFAULT_CHAT_PROVIDER = "gemini"
+DEFAULT_CHAT_MODEL = "Gemini Flash 2.5"
+DEFAULT_FAST_CHAT_PROVIDER = "gemini"
+DEFAULT_FAST_CHAT_MODEL = "Gemini Flash 2.5"
+DEFAULT_EMBEDDING_PROVIDER = "openai"
+DEFAULT_EMBEDDING_MODEL = "Text embedding 3 large"

packages/agents/src/core/agentFactory.ts

@@ -3,6 +3,7 @@ import { Embeddings } from '@langchain/core/embeddings';
 import { getAgentConfig } from '../config/agent';
 import EventEmitter from 'events';
 import { RagPipeline } from './pipeline/ragPipeline';
+import { McpPipeline } from './pipeline/mcpPipeline';
 import { VectorStore } from '../db/postgresVectorStore';
 import { LLMConfig } from '../types';
 
@@ -13,9 +14,12 @@ export class RagAgentFactory {
     llm: LLMConfig,
     embeddings: Embeddings,
     vectorStore: VectorStore,
+    mcpMode: boolean = false,
   ): EventEmitter {
     const config = getAgentConfig(vectorStore);
-    const pipeline = new RagPipeline(llm, embeddings, config);
+    const pipeline = mcpMode 
+      ? new McpPipeline(llm, embeddings, config)
+      : new RagPipeline(llm, embeddings, config);
     return pipeline.execute({
       query: message,
       chatHistory: history,

packages/agents/src/core/pipeline/mcpPipeline.ts

@@ -0,0 +1,62 @@
+import { RagPipeline } from './ragPipeline';
+import { RagInput, StreamHandler } from '../../types';
+import { logger, TokenTracker } from '../../utils';
+
+/**
+ * MCP Pipeline that extends RAG pipeline but stops at document retrieval
+ * without generating answers, returning raw documents instead.
+ */
+export class McpPipeline extends RagPipeline {
+  protected async runPipeline(
+    input: RagInput,
+    handler: StreamHandler,
+  ): Promise<void> {
+    try {
+      // Reset token counters at the start of each pipeline run
+      TokenTracker.resetSessionCounters();
+
+      logger.info('Starting MCP pipeline', { query: input.query });
+
+      // Step 1: Process the query
+      const processedQuery = await this.queryProcessor.process(input);
+      logger.debug('Processed query:', processedQuery);
+
+      // Step 2: Retrieve documents
+      const retrieved = await this.documentRetriever.retrieve(
+        processedQuery,
+        input.sources,
+      );
+      handler.emitSources(retrieved.documents);
+
+      // Step 3: Return raw documents without answer generation
+      logger.info('MCP mode - returning raw documents');
+
+      const rawDocuments = retrieved.documents.map(doc => ({
+        pageContent: doc.pageContent,
+        metadata: doc.metadata
+      }));
+
+      handler.emitResponse({
+        content: JSON.stringify(rawDocuments, null, 2),
+      } as any);
+
+      logger.debug('MCP pipeline ended');
+
+      // Log final token usage
+      const tokenUsage = TokenTracker.getSessionTokenUsage();
+      logger.info('MCP Pipeline completed', { 
+        query: input.query,
+        tokenUsage: {
+          promptTokens: tokenUsage.promptTokens,
+          responseTokens: tokenUsage.responseTokens,
+          totalTokens: tokenUsage.totalTokens
+        }
+      });
+
+      handler.emitEnd();
+    } catch (error) {
+      logger.error('MCP Pipeline error:', error);
+      handler.emitError('An error occurred while processing your request');
+    }
+  }
+} 

packages/agents/src/core/pipeline/ragPipeline.ts

@@ -10,9 +10,9 @@ import { logger, TokenTracker } from '../../utils';
  * Orchestrates the RAG process in a clear, sequential flow.
  */
 export class RagPipeline {
-  private queryProcessor: QueryProcessor;
-  private documentRetriever: DocumentRetriever;
-  private answerGenerator: AnswerGenerator;
+  protected queryProcessor: QueryProcessor;
+  protected documentRetriever: DocumentRetriever;
+  protected answerGenerator: AnswerGenerator;
 
   constructor(
     private llmConfig: LLMConfig,
@@ -41,7 +41,7 @@ export class RagPipeline {
     return emitter;
   }
 
-  private async runPipeline(
+  protected async runPipeline(
     input: RagInput,
     handler: StreamHandler,
   ): Promise<void> {

packages/backend/src/routes/cairocoder.ts

@@ -52,6 +52,9 @@ router.post('/', async (req, res) => {
       });
     }
 
+    // Check for MCP mode header
+    const mcpMode = req.headers['mcp'] === 'true';
+
     // Convert messages to LangChain format
     const langChainMessages = convertToLangChainMessages(messages);
 
@@ -86,6 +89,7 @@ router.post('/', async (req, res) => {
       llmConfig,
       embeddings,
       vectorStore,
+      mcpMode,
     );
 
     if (stream) {