Feature/react call mcp (#428)

Key Features

  - MCP Tool Integration: Added core MCP tool support with ToolClientSpec and ToolClient classes
  - API Enhancement: New mcp_tool method for flow-specific tool invocation
  - CLI Tooling: New tg-invoke-mcp-tool command for testing MCP integration
  - React Agent Enhancement: Fixed and improved multi-tool invocation capabilities
  - Tool Management: Enhanced CLI for tool configuration and management

Changes

  - Added MCP tool invocation to API with flow-specific integration
  - Implemented ToolClientSpec and ToolClient for tool call handling
  - Updated agent-manager-react to invoke MCP tools with configurable types
  - Enhanced CLI with new commands and improved help text
  - Added comprehensive documentation for new CLI commands
  - Improved tool configuration management

Testing

  - Added tg-invoke-mcp-tool CLI command for isolated MCP integration testing
  - Enhanced agent capability to invoke multiple tools simultaneously

trustgraph-flow/trustgraph/agent/react/agent_manager.py

@@ -14,12 +14,19 @@ class AgentManager:
 
     async def reason(self, question, history, context):
 
+        print(f"calling reason: {question}", flush=True)
+
         tools = self.tools
 
+        print(f"in reason", flush=True)
+        print(tools, flush=True)
+
         tool_names = ",".join([
             t for t in self.tools.keys()
         ])
 
+        print("Tool names:", tool_names, flush=True)
+
         variables = {
             "question": question,
             "tools": [
@@ -83,6 +90,9 @@ class AgentManager:
 
     async def react(self, question, history, think, observe, context):
 
+        logger.info(f"question: {question}")
+        print(f"question: {question}", flush=True)
+
         act = await self.reason(
             question = question,
             history = history,
@@ -104,13 +114,12 @@ class AgentManager:
             else:
                 raise RuntimeError(f"No action for {act.name}!")
 
-            print("TOOL>>>", act)
+            print("TOOL>>>", act, flush=True)
+
             resp = await action.implementation(context).invoke(
                 **act.arguments
             )
 
-            print("RSETUL", resp)
-
             resp = resp.strip()
 
             logger.info(f"resp: {resp}")

trustgraph-flow/trustgraph/agent/react/service.py

@@ -5,13 +5,14 @@ Simple agent infrastructure broadly implements the ReAct flow.
 import json
 import re
 import sys
+import functools
 
 from ... base import AgentService, TextCompletionClientSpec, PromptClientSpec
-from ... base import GraphRagClientSpec
+from ... base import GraphRagClientSpec, ToolClientSpec
 
 from ... schema import AgentRequest, AgentResponse, AgentStep, Error
 
-from . tools import KnowledgeQueryImpl, TextCompletionImpl
+from . tools import KnowledgeQueryImpl, TextCompletionImpl, McpToolImpl
 from . agent_manager import AgentManager
 
 from . types import Final, Action, Tool, Argument
@@ -67,6 +68,13 @@ class Processor(AgentService):
             )
         )
 
+        self.register_specification(
+            ToolClientSpec(
+                request_name = "mcp-tool-request",
+                response_name = "mcp-tool-response",
+            )
+        )
+
     async def on_tools_config(self, config, version):
 
         print("Loading configuration version", version)
@@ -102,17 +110,21 @@ class Processor(AgentService):
 
                 impl_id = data.get("type")
 
+                name = data.get("name")
+
                 if impl_id == "knowledge-query":
                     impl = KnowledgeQueryImpl
                 elif impl_id == "text-completion":
                     impl = TextCompletionImpl
+                elif impl_id == "mcp-tool":
+                    impl = functools.partial(McpToolImpl, name=k)
                 else:
                     raise RuntimeError(
                         f"Tool-kind {impl_id} not known"
                     )
 
                 tools[data.get("name")] = Tool(
-                    name = data.get("name"),
+                    name = name,
                     description = data.get("description"),
                     implementation = impl,
                     config=data.get("config", {}),
@@ -181,6 +193,8 @@ class Processor(AgentService):
 
                 await respond(r)
 
+            print("Call React", flush=True)
+
             act = await self.agent.react(
                 question = request.question,
                 history = history,

trustgraph-flow/trustgraph/agent/react/tools.py

@@ -1,4 +1,6 @@
 
+import json
+
 # This tool implementation knows how to put a question to the graph RAG
 # service
 class KnowledgeQueryImpl:
@@ -23,3 +25,29 @@ class TextCompletionImpl:
             arguments.get("question")
         )
 
+# This tool implementation knows how to do MCP tool invocation.  This uses
+# the mcp-tool service.
+class McpToolImpl:
+
+    def __init__(self, context, name):
+        self.context = context
+        self.name = name
+
+    async def invoke(self, **arguments):
+
+        client = self.context("mcp-tool-request")
+
+        print(f"MCP tool invocation: {self.name}...", flush=True)
+        output = await client.invoke(
+            name = self.name,
+            parameters = {},
+        )
+
+        print(output)
+
+        if isinstance(output, str):
+            return output
+        else:
+            return json.dumps(output)
+
+