Agent call to mcp-tool is working with a hard-coded service.

- Added ToolClientSpec and ToolClient to implement a tool call.
- Updated agent-manager-react to invoke an MCP tool with a tool defined
  with 'mcp-tool' type.
Not generic, need to work out how to call the right parameters.

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

@@ -7,11 +7,11 @@ import re
 import sys
 
 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 +67,13 @@ 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)
@@ -106,6 +113,8 @@ class Processor(AgentService):
                     impl = KnowledgeQueryImpl
                 elif impl_id == "text-completion":
                     impl = TextCompletionImpl
+                elif impl_id == "mcp-tool":
+                    impl = McpToolImpl
                 else:
                     raise RuntimeError(
                         f"Tool-kind {impl_id} not known"
@@ -181,6 +190,8 @@ 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

@@ -23,3 +23,22 @@ 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):
+        self.context = context
+    async def invoke(self, **arguments):
+        client = self.context("mcp-tool-request")
+        print("MCP tool invocation...", flush=True)
+        output = await client.invoke(
+            name = "time",
+            parameters = {},
+        )
+
+        print(output)
+
+        print(type(output))
+
+        return output["result"]
+