add MCP raw filter support: body+path args, update mcp_filter demo handlers

config/plano_config_schema.yaml

@@ -85,7 +85,7 @@ properties:
                     type: string
                   default:
                     type: boolean
-                  filter_chain:
+                  input_filters:
                     type: array
                     items:
                       type: string

crates/brightstaff/src/handlers/agent_chat_completions.rs

@@ -332,16 +332,39 @@ async fn handle_agent_chat_inner(
             "processing agent"
         );
 
-        // Process the filter chain
+        // Process input filters — serialize current request as OpenAI chat completions body,
-        let chat_history = pipeline_processor
+        // pass raw bytes through each filter, then extract updated messages from the result.
-            .process_filter_chain(
+        let chat_history = if selected_agent
-                &current_messages,
+            .input_filters
+            .as_ref()
+            .map(|f| !f.is_empty())
+            .unwrap_or(false)
+        {
+            let filter_body = serde_json::json!({
+                "model": client_request.model(),
+                "messages": current_messages,
+            });
+            let filter_bytes =
+                serde_json::to_vec(&filter_body).map_err(PipelineError::ParseError)?;
+
+            let filtered_bytes = pipeline_processor
+                .process_raw_filter_chain(
+                    &filter_bytes,
                     selected_agent,
                     &agent_map,
                     &request_headers,
+                    "/v1/chat/completions",
                 )
                 .await?;
 
+            let filtered_body: serde_json::Value =
+                serde_json::from_slice(&filtered_bytes).map_err(PipelineError::ParseError)?;
+            serde_json::from_value(filtered_body["messages"].clone())
+                .map_err(PipelineError::ParseError)?
+        } else {
+            current_messages.clone()
+        };
+
         // Get agent details and invoke
         let agent = agent_map.get(&agent_name).unwrap();
 

crates/brightstaff/src/handlers/agent_selector.rs

@@ -187,7 +187,7 @@ mod tests {
             id: name.to_string(),
             description: Some(description.to_string()),
             default: Some(is_default),
-            filter_chain: Some(vec![name.to_string()]),
+            input_filters: Some(vec![name.to_string()]),
         }
     }
 

crates/brightstaff/src/handlers/integration_tests.rs

@@ -64,7 +64,7 @@ mod tests {
 
         let agent_pipeline = AgentFilterChain {
             id: "terminal-agent".to_string(),
-            filter_chain: Some(vec![
+            input_filters: Some(vec![
                 "filter-agent".to_string(),
                 "terminal-agent".to_string(),
             ]),
@@ -110,7 +110,7 @@ mod tests {
         // Create a pipeline with empty filter chain to avoid network calls
         let test_pipeline = AgentFilterChain {
             id: "terminal-agent".to_string(),
-            filter_chain: Some(vec![]), // Empty filter chain - no network calls needed
+            input_filters: Some(vec![]), // Empty filter chain - no network calls needed
             description: None,
             default: None,
         };

crates/brightstaff/src/handlers/llm.rs

@@ -279,7 +279,7 @@ async fn llm_chat_inner(
                     id: "model_listener".to_string(),
                     default: None,
                     description: None,
-                    filter_chain: Some(fc.clone()),
+                    input_filters: Some(fc.clone()),
                 };
 
                 let mut pipeline_processor = PipelineProcessor::default();

crates/brightstaff/src/handlers/pipeline_processor.rs

@@ -84,7 +84,7 @@ impl PipelineProcessor {
     // #[instrument(
     //     skip(self, chat_history, agent_filter_chain, agent_map, request_headers),
     //     fields(
-    //         filter_count = agent_filter_chain.filter_chain.as_ref().map(|fc| fc.len()).unwrap_or(0),
+    //         filter_count = agent_filter_chain.input_filters.as_ref().map(|fc| fc.len()).unwrap_or(0),
     //         message_count = chat_history.len()
     //     )
     // )]
@@ -99,7 +99,7 @@ impl PipelineProcessor {
         let mut chat_history_updated = chat_history.to_vec();
 
         // If filter_chain is None or empty, proceed without filtering
-        let filter_chain = match agent_filter_chain.filter_chain.as_ref() {
+        let filter_chain = match agent_filter_chain.input_filters.as_ref() {
             Some(fc) if !fc.is_empty() => fc,
             _ => return Ok(chat_history_updated),
         };
@@ -283,6 +283,30 @@ impl PipelineProcessor {
         })
     }
 
+    /// Build a tools/call JSON-RPC request with a full body dict and path hint.
+    /// Used by execute_mcp_filter_raw so MCP tools receive the same contract as HTTP filters.
+    fn build_tool_call_request_with_body(
+        &self,
+        tool_name: &str,
+        body: &serde_json::Value,
+        path: &str,
+    ) -> Result<JsonRpcRequest, PipelineError> {
+        let mut arguments = HashMap::new();
+        arguments.insert("body".to_string(), serde_json::to_value(body)?);
+        arguments.insert("path".to_string(), serde_json::to_value(path)?);
+
+        let mut params = HashMap::new();
+        params.insert("name".to_string(), serde_json::to_value(tool_name)?);
+        params.insert("arguments".to_string(), serde_json::to_value(arguments)?);
+
+        Ok(JsonRpcRequest {
+            jsonrpc: JSON_RPC_VERSION.to_string(),
+            id: JsonRpcId::String(Uuid::new_v4().to_string()),
+            method: TOOL_CALL_METHOD.to_string(),
+            params: Some(params),
+        })
+    }
+
     /// Send request to a specific agent and return the response content
     #[instrument(
         skip(self, messages, agent, request_headers),
@@ -406,6 +430,106 @@ impl PipelineProcessor {
         Ok(messages)
     }
 
+    /// Like execute_mcp_filter but passes the full raw body dict + path hint as MCP tool arguments.
+    /// The MCP tool receives (body: dict, path: str) and returns the modified body dict.
+    async fn execute_mcp_filter_raw(
+        &mut self,
+        raw_bytes: &[u8],
+        agent: &Agent,
+        request_headers: &HeaderMap,
+        request_path: &str,
+    ) -> Result<Bytes, PipelineError> {
+        set_service_name(operation_component::AGENT_FILTER);
+        use opentelemetry::trace::get_active_span;
+        get_active_span(|span| {
+            span.update_name(format!("execute_mcp_filter_raw ({})", agent.id));
+        });
+
+        let body: serde_json::Value =
+            serde_json::from_slice(raw_bytes).map_err(PipelineError::ParseError)?;
+
+        let mcp_session_id = if let Some(session_id) = self.agent_id_session_map.get(&agent.id) {
+            session_id.clone()
+        } else {
+            let session_id = self.get_new_session_id(&agent.id, request_headers).await;
+            self.agent_id_session_map
+                .insert(agent.id.clone(), session_id.clone());
+            session_id
+        };
+
+        info!(
+            "Using MCP session ID {} for agent {}",
+            mcp_session_id, agent.id
+        );
+
+        let tool_name = agent.tool.as_deref().unwrap_or(&agent.id);
+        let json_rpc_request =
+            self.build_tool_call_request_with_body(tool_name, &body, request_path)?;
+
+        let agent_headers =
+            self.build_mcp_headers(request_headers, &agent.id, Some(&mcp_session_id))?;
+
+        let response = self
+            .send_mcp_request(&json_rpc_request, &agent_headers, &agent.id)
+            .await?;
+        let http_status = response.status();
+        let response_bytes = response.bytes().await?;
+
+        if !http_status.is_success() {
+            let error_body = String::from_utf8_lossy(&response_bytes).to_string();
+            return Err(if http_status.is_client_error() {
+                PipelineError::ClientError {
+                    agent: agent.id.clone(),
+                    status: http_status.as_u16(),
+                    body: error_body,
+                }
+            } else {
+                PipelineError::ServerError {
+                    agent: agent.id.clone(),
+                    status: http_status.as_u16(),
+                    body: error_body,
+                }
+            });
+        }
+
+        let data_chunk = self.parse_sse_response(&response_bytes, &agent.id)?;
+        let response: JsonRpcResponse = serde_json::from_str(&data_chunk)?;
+        let response_result = response
+            .result
+            .ok_or_else(|| PipelineError::NoResultInResponse(agent.id.clone()))?;
+
+        if response_result
+            .get("isError")
+            .and_then(|v| v.as_bool())
+            .unwrap_or(false)
+        {
+            let error_message = response_result
+                .get("content")
+                .and_then(|v| v.as_array())
+                .and_then(|arr| arr.first())
+                .and_then(|v| v.get("text"))
+                .and_then(|v| v.as_str())
+                .unwrap_or("unknown_error")
+                .to_string();
+
+            return Err(PipelineError::ClientError {
+                agent: agent.id.clone(),
+                status: hyper::StatusCode::BAD_REQUEST.as_u16(),
+                body: error_message,
+            });
+        }
+
+        let result = response_result
+            .get("structuredContent")
+            .and_then(|v| v.get("result"))
+            .cloned()
+            .ok_or_else(|| PipelineError::NoStructuredContentInResponse(agent.id.clone()))?;
+
+        Ok(Bytes::from(
+            serde_json::to_vec(&result).map_err(PipelineError::ParseError)?,
+        ))
+    }
+
     /// Build an initialize JSON-RPC request
     fn build_initialize_request(&self) -> JsonRpcRequest {
         JsonRpcRequest {
@@ -708,7 +832,7 @@ impl PipelineProcessor {
         request_headers: &HeaderMap,
         request_path: &str,
     ) -> Result<Bytes, PipelineError> {
-        let filter_chain = match agent_filter_chain.filter_chain.as_ref() {
+        let filter_chain = match agent_filter_chain.input_filters.as_ref() {
             Some(fc) if !fc.is_empty() => fc,
             _ => return Ok(Bytes::copy_from_slice(raw_bytes)),
         };
@@ -722,16 +846,22 @@ impl PipelineProcessor {
                 .get(agent_name)
                 .ok_or_else(|| PipelineError::AgentNotFound(agent_name.clone()))?;
 
+            let agent_type = agent.agent_type.as_deref().unwrap_or("mcp");
             info!(
                 agent = %agent_name,
                 url = %agent.url,
+                agent_type = %agent_type,
                 bytes_len = current_bytes.len(),
                 "executing raw filter"
             );
 
-            current_bytes = self
+            current_bytes = if agent_type == "mcp" {
-                .execute_raw_filter(&current_bytes, agent, request_headers, request_path)
+                self.execute_mcp_filter_raw(&current_bytes, agent, request_headers, request_path)
-                .await?;
+                    .await?
+            } else {
+                self.execute_raw_filter(&current_bytes, agent, request_headers, request_path)
+                    .await?
+            };
 
             info!(agent = %agent_name, bytes_len = current_bytes.len(), "raw filter completed");
         }
@@ -812,7 +942,7 @@ mod tests {
     fn create_test_pipeline(agents: Vec<&str>) -> AgentFilterChain {
         AgentFilterChain {
             id: "test-agent".to_string(),
-            filter_chain: Some(agents.iter().map(|s| s.to_string()).collect()),
+            input_filters: Some(agents.iter().map(|s| s.to_string()).collect()),
             description: None,
             default: None,
         }

crates/brightstaff/src/handlers/utils.rs

@@ -308,7 +308,7 @@ where
                 id: "output_filter".to_string(),
                 default: None,
                 description: None,
-                filter_chain: Some(output_filters),
+                input_filters: Some(output_filters),
             };
 
             while let Some(item) = byte_stream.next().await {

crates/common/src/configuration.rs

@@ -27,7 +27,7 @@ pub struct AgentFilterChain {
     pub id: String,
     pub default: Option<bool>,
     pub description: Option<String>,
-    pub filter_chain: Option<Vec<String>>,
+    pub input_filters: Option<Vec<String>>,
 }
 
 #[derive(Debug, Clone, Serialize, Deserialize, PartialEq, Eq)]

demos/filter_chains/http_filter/config.yaml

@@ -42,7 +42,7 @@ listeners:
     agents:
       - id: rag_agent
         description: virtual assistant for retrieval augmented generation tasks
-        filter_chain:
+        input_filters:
           - input_guards
           - query_rewriter
           - context_builder

demos/filter_chains/http_filter/src/rag_agent/context_builder.py

@@ -195,11 +195,11 @@ async def augment_query_with_context(
 load_knowledge_base()
 
 
-@app.post("/")
+@app.post("/{path:path}")
-async def context_builder(
+async def context_builder(path: str, request: Request) -> dict:
-    messages: List[ChatMessage], request: Request
-) -> List[ChatMessage]:
     """MCP tool that augments user queries with relevant context from the knowledge base."""
+    body = await request.json()
+    messages = [ChatMessage(**m) for m in body.get("messages", [])]
     logger.info(f"Received chat completion request with {len(messages)} messages")
 
     # Get traceparent header from MCP request
@@ -219,8 +219,7 @@ async def context_builder(
         messages, traceparent_header, request_id
     )
 
-    # Return as dict to minimize text serialization
+    return {**body, "messages": [{"role": msg.role, "content": msg.content} for msg in updated_messages]}
-    return [{"role": msg.role, "content": msg.content} for msg in updated_messages]
 
 
 # Register MCP tool only if mcp is available

demos/filter_chains/http_filter/src/rag_agent/input_guards.py

@@ -126,14 +126,14 @@ Respond in JSON format:
 
 
 # @mcp.tool
-@app.post("/")
+@app.post("/{path:path}")
-async def input_guards(
+async def input_guards(path: str, request: Request) -> dict:
-    messages: List[ChatMessage], request: Request
-) -> List[ChatMessage]:
     """Input guard that validates queries are within TechCorp's domain.
 
     If the query is out of scope, replaces the user message with a rejection notice.
     """
+    body = await request.json()
+    messages = [ChatMessage(**m) for m in body.get("messages", [])]
     logger.info(f"Received request with {len(messages)} messages")
 
     # Get traceparent header from HTTP request using FastMCP's dependency function
@@ -164,7 +164,7 @@ async def input_guards(
         )
 
     logger.info("Query validation passed - forwarding to next filter")
-    return messages
+    return body
 
 
 @app.get("/health")

demos/filter_chains/http_filter/src/rag_agent/query_rewriter.py

@@ -81,11 +81,11 @@ Return only the rewritten query, nothing else."""
     return ""
 
 
-@app.post("/")
+@app.post("/{path:path}")
-async def query_rewriter_http(
+async def query_rewriter_http(path: str, request: Request) -> dict:
-    messages: List[ChatMessage], request: Request
-) -> List[ChatMessage]:
     """HTTP filter endpoint used by Plano (type: http)."""
+    body = await request.json()
+    messages = [ChatMessage(**m) for m in body.get("messages", [])]
     logger.info(f"Received request with {len(messages)} messages")
 
     traceparent_header = request.headers.get("traceparent")
@@ -99,25 +99,20 @@ async def query_rewriter_http(
     rewritten_query = await rewrite_query_with_plano(
         messages, traceparent_header, request_id
     )
-    # Create updated messages with the rewritten query
-    updated_messages = messages.copy()
 
     # Find and update the last user message with the rewritten query
+    updated_messages = [m.model_dump() for m in messages]
     for i in range(len(updated_messages) - 1, -1, -1):
-        if updated_messages[i].role == "user":
+        if updated_messages[i]["role"] == "user":
-            original_query = updated_messages[i].content
+            original_query = updated_messages[i]["content"]
-            updated_messages[i] = ChatMessage(role="user", content=rewritten_query)
+            updated_messages[i]["content"] = rewritten_query
             logger.info(
                 f"Updated user query from '{original_query}' to '{rewritten_query}'"
             )
             break
-    updated_messages_data = [
-        {"role": msg.role, "content": msg.content} for msg in updated_messages
-    ]
-    updated_messages = [ChatMessage(**msg) for msg in updated_messages_data]
 
     logger.info("Returning rewritten chat completion response")
-    return updated_messages
+    return {**body, "messages": updated_messages}
 
 
 @app.get("/health")

demos/filter_chains/mcp_filter/config.yaml

@@ -39,7 +39,7 @@ listeners:
     agents:
       - id: rag_agent
         description: virtual assistant for retrieval augmented generation tasks
-        filter_chain:
+        input_filters:
           - input_guards
           - query_rewriter
           - context_builder

demos/filter_chains/mcp_filter/src/rag_agent/context_builder.py

@@ -195,9 +195,14 @@ async def augment_query_with_context(
 load_knowledge_base()
 
 
-async def context_builder(messages: List[ChatMessage]) -> List[ChatMessage]:
+async def context_builder(body: dict, path: str) -> dict:
-    """MCP tool that augments user queries with relevant context from the knowledge base."""
+    """MCP tool that augments user queries with relevant context from the knowledge base.
-    logger.info(f"Received chat completion request with {len(messages)} messages")
+
+    Receives the full request body dict and the API path hint (e.g. /v1/chat/completions).
+    Returns the body with the last user message augmented with retrieved context.
+    """
+    messages = [ChatMessage(**m) for m in body.get("messages", [])]
+    logger.info(f"Received request with {len(messages)} messages at path {path}")
 
     # Get traceparent header from MCP request
     headers = get_http_headers()
@@ -215,8 +220,7 @@ async def context_builder(messages: List[ChatMessage]) -> List[ChatMessage]:
         messages, traceparent_header, request_id
     )
 
-    # Return as dict to minimize text serialization
+    return {**body, "messages": [{"role": msg.role, "content": msg.content} for msg in updated_messages]}
-    return [{"role": msg.role, "content": msg.content} for msg in updated_messages]
 
 
 # Register MCP tool only if mcp is available

demos/filter_chains/mcp_filter/src/rag_agent/input_guards.py

@@ -3,13 +3,12 @@ import json
 import time
 from typing import List, Optional, Dict, Any
 import uuid
-from fastapi import FastAPI, Depends, Request
 from fastmcp.exceptions import ToolError
 from openai import AsyncOpenAI
 import os
 import logging
 
-from .api import ChatCompletionRequest, ChatCompletionResponse, ChatMessage
+from .api import ChatMessage
 from . import mcp
 from fastmcp.server.dependencies import get_http_headers
 
@@ -30,8 +29,6 @@ plano_client = AsyncOpenAI(
     api_key="EMPTY",  # Plano doesn't require a real API key
 )
 
-app = FastAPI()
-
 
 async def validate_query_scope(
     messages: List[ChatMessage],
@@ -127,12 +124,14 @@ Respond in JSON format:
 
 
 @mcp.tool
-async def input_guards(messages: List[ChatMessage]) -> List[ChatMessage]:
+async def input_guards(body: dict, path: str) -> dict:
     """Input guard that validates queries are within TechCorp's domain.
 
-    If the query is out of scope, replaces the user message with a rejection notice.
+    Receives the full request body dict and the API path hint (e.g. /v1/chat/completions).
+    If the query is out of scope, raises a ToolError to block the request.
     """
-    logger.info(f"Received request with {len(messages)} messages")
+    messages = [ChatMessage(**m) for m in body.get("messages", [])]
+    logger.info(f"Received request with {len(messages)} messages at path {path}")
 
     # Get traceparent header from HTTP request using FastMCP's dependency function
     headers = get_http_headers()
@@ -153,9 +152,8 @@ async def input_guards(messages: List[ChatMessage]) -> List[ChatMessage]:
         reason = validation_result.get("reason", "Query is outside TechCorp's domain")
         logger.warning(f"Query rejected: {reason}")
 
-        # Throw ToolError
         error_message = f"I apologize, but I can only assist with questions related to TechCorp and its services. Your query appears to be outside this scope. {reason}\n\nPlease ask me about TechCorp's products, services, pricing, SLAs, or technical support."
         raise ToolError(error_message)
 
     logger.info("Query validation passed - forwarding to next filter")
-    return messages
+    return body

demos/filter_chains/mcp_filter/src/rag_agent/query_rewriter.py

@@ -3,12 +3,11 @@ import json
 import time
 from typing import List, Optional, Dict, Any
 import uuid
-from fastapi import FastAPI, Depends, Request
 from openai import AsyncOpenAI
 import os
 import logging
 
-from .api import ChatCompletionRequest, ChatCompletionResponse, ChatMessage
+from .api import ChatMessage
 from . import mcp
 from fastmcp.server.dependencies import get_http_headers
 
@@ -29,9 +28,6 @@ plano_client = AsyncOpenAI(
     api_key="EMPTY",  # Plano doesn't require a real API key
 )
 
-app = FastAPI()
-
-
 async def rewrite_query_with_plano(
     messages: List[ChatMessage],
     traceparent_header: str,
@@ -87,12 +83,14 @@ async def rewrite_query_with_plano(
     return ""
 
 
-async def query_rewriter(messages: List[ChatMessage]) -> List[ChatMessage]:
+async def query_rewriter(body: dict, path: str) -> dict:
-    """Chat completions endpoint that rewrites the last user query using Plano.
+    """Rewrites the last user query in the request body using Plano.
 
-    Returns a dict with a 'messages' key containing the updated message list.
+    Receives the full request body dict and the API path hint (e.g. /v1/chat/completions).
+    Returns the body with the last user message rewritten for better retrieval.
     """
-    logger.info(f"Received chat completion request with {len(messages)} messages")
+    messages = [ChatMessage(**m) for m in body.get("messages", [])]
+    logger.info(f"Received request with {len(messages)} messages at path {path}")
 
     # Get traceparent header from HTTP request using FastMCP's dependency function
     headers = get_http_headers()
@@ -109,57 +107,20 @@ async def query_rewriter(messages: List[ChatMessage]) -> List[ChatMessage]:
         messages, traceparent_header, request_id
     )
 
-    # Create updated messages with the rewritten query
-    updated_messages = messages.copy()
-
     # Find and update the last user message with the rewritten query
+    updated_messages = [m.model_dump() for m in messages]
     for i in range(len(updated_messages) - 1, -1, -1):
-        if updated_messages[i].role == "user":
+        if updated_messages[i]["role"] == "user":
-            original_query = updated_messages[i].content
-            updated_messages[i] = ChatMessage(role="user", content=rewritten_query)
             logger.info(
-                f"Updated user query from '{original_query}' to '{rewritten_query}'"
+                f"Updated user query from '{updated_messages[i]['content']}' to '{rewritten_query}'"
             )
+            updated_messages[i]["content"] = rewritten_query
             break
 
-    # Return as dict to minimize text serialization
+    logger.info("Returning rewritten chat completion response")
-    return [{"role": msg.role, "content": msg.content} for msg in updated_messages]
+    return {**body, "messages": updated_messages}
 
 
 # Register MCP tool only if mcp is available
 if mcp is not None:
     mcp.tool()(query_rewriter)
-
-
-@app.post("/")
-async def chat_completions_endpoint(
-    request_messages: List[ChatMessage], request: Request
-) -> List[ChatMessage]:
-    """FastAPI endpoint for chat completions with query rewriting."""
-    logger.info(
-        f"Received /v1/chat/completions request with {len(request_messages)} messages"
-    )
-
-    # Extract traceparent header
-    traceparent_header = request.headers.get("traceparent")
-    if traceparent_header:
-        logger.info(f"Received traceparent header: {traceparent_header}")
-    else:
-        logger.info("No traceparent header found")
-
-    # Call the query rewriter tool
-    updated_messages_data = await query_rewriter(request_messages)
-
-    # Convert back to ChatMessage objects
-    updated_messages = [ChatMessage(**msg) for msg in updated_messages_data]
-
-    logger.info("Returning rewritten chat completion response")
-    return updated_messages
-
-
-def start_server(host: str = "0.0.0.0", port: int = 10501):
-    """Start the FastAPI server for query rewriter."""
-    import uvicorn
-
-    logger.info(f"Starting Query Rewriter REST server on {host}:{port}")
-    uvicorn.run(app, host=host, port=port)