Streaming End-to-End MCP Tool Use with an AI Model

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Demonstrates Ai.UseMcp in a streaming Model Context Protocol (MCP) workflow. This is the same idea as the non-streaming MCP example, but the answer is streamed token-by-token and the automatic MCP tool call is driven by the application's event loop rather than happening invisibly inside Ask.

A tool-using conversation spans more than one streamed turn. In the first turn the model streams a js_function_call event; the example hands that event's JSON to StreamingJsToolCall, which routes MCP tools to the server and appends the result to the transcript, and the turn ends with null_terminator. The example then calls Ask again (with no new input, since the tool result is already in the transcript) so the model can continue and stream its final answer. The loop ends when a streamed turn finishes with no tool call outstanding.

Tip: Code to parse the returned JSON can be generated with Chilkat's online tool at https://tools.chilkat.io/jsonParse.

#import <CkoMcp.h>
#import <CkoAi.h>
#import <CkoStringBuilder.h>
#import <CkoJsonObject.h>

BOOL success = NO;

//  Streaming, end-to-end MCP example.  Same idea as the non-streaming MCP example, but the answer is
//  streamed token-by-token, and the automatic MCP tool call is driven by the application's event loop
//  instead of happening invisibly inside Ask.
//  
//  A tool-using conversation spans more than one streamed turn:
//  
//    turn 1:  the model streams a "js_function_call" event (it wants a tool).  We hand that event's
//             JSON to StreamingJsToolCall, which routes MCP tools to the server (Mcp.CallTool) and
//             appends the result to the transcript.  The turn then ends with "null_terminator".
//    turn 2:  we call Ask again (no new input -- the tool result is already in the transcript) so the
//             model can continue.  It streams the final answer and ends with "null_terminator", with
//             no pending tool call.
//  
//  The loop ends when a streamed turn finishes with no tool call outstanding.
//  
//  MCP server: DeepWiki -- a free, public, no-authentication Streamable HTTP server that answers
//  questions about public GitHub repositories.  Swap in any URL; set mcp.AuthToken before Connect if
//  it needs a bearer token.

//  1) Connect to the MCP server.
CkoMcp *mcp = [[CkoMcp alloc] init];
//  mcp.AuthToken = "...";   // <-- only if the server requires a bearer token
success = [mcp Connect: @"https://mcp.deepwiki.com/mcp"];
if (success == NO) {
    NSLog(@"%@",mcp.LastErrorText);
    return;
}

NSLog(@"%@%@%@%@%@",@"Connected to MCP server: ",mcp.ServerName,@" (version ",mcp.ServerVersion,@")");

//  2) Set up the AI conversation and register the MCP tools.
CkoAi *ai = [[CkoAi alloc] init];
ai.Provider = @"anthropic";
//  The API key should come from a secure source rather than being hard-coded.
ai.ApiKey = @"AI_PROVIDER_API_KEY";
ai.Model = @"claude-sonnet-5";

//  Automatic tool use requires a conversation (not a stateless query).
success = [ai NewConvo: @"test_conversation" sysMsg: @"You are a helpful assistant.  Use the available tools when they can help answer the question." devMsg: @""];
if (success == NO) {
    NSLog(@"%@",ai.LastErrorText);
    return;
}

//  Namespace the server's tools with "deepwiki" -- e.g. "deepwiki_ask_question".  The Mcp object must
//  stay connected and in scope for the whole conversation.
success = [ai UseMcp: mcp namePrefix: @"deepwiki"];
if (success == NO) {
    NSLog(@"%@",ai.LastErrorText);
    return;
}

//  Multiple MCP servers can be used in the same conversation.  Connect each server and call UseMcp
//  once per server, giving each a distinct prefix so their tool names cannot collide.  For example:
//      success = ai.UseMcp(mcpWeather,"weather");
//      success = ai.UseMcp(mcpGitHub,"github");

success = [ai InputAddText: @"Use the available tools to look up the GitHub repository \"modelcontextprotocol/modelcontextprotocol\", then give me a brief, sourced summary of which transports the Model Context Protocol defines."];
if (success == NO) {
    NSLog(@"%@",ai.LastErrorText);
    return;
}

//  3) Start streaming.
ai.Streaming = YES;
success = [ai Ask: @"text"];
if (success == NO) {
    NSLog(@"%@",ai.LastErrorText);
    return;
}

//  4) Drive the streaming event loop.
CkoStringBuilder *sbEventName = [[CkoStringBuilder alloc] init];
CkoStringBuilder *sbDelta = [[CkoStringBuilder alloc] init];
CkoStringBuilder *sbFullResponse = [[CkoStringBuilder alloc] init];
BOOL bConversationDone = NO;
BOOL bToolCallPending = NO;
BOOL bCaseSensitive = YES;
BOOL bAbort = NO;
int loopGuard = 0;
int result = 0;

while ((bConversationDone != YES) && (loopGuard < 8000)) {
    loopGuard = loopGuard + 1;
    result = [[ai PollAi: bAbort] intValue];
    if (result < 0) {
        NSLog(@"%@",ai.LastErrorText);
        return;
    }

    if (result == 0) {
        //  No event ready yet.
        [ai SleepMs: [NSNumber numberWithInt: 100]];
    }
    else {
        success = [ai NextAiEvent: [NSNumber numberWithInt: 5000] sbName: sbEventName sbDelta: sbDelta];
        if (success == NO) {
            NSLog(@"%@",ai.LastErrorText);
            return;
        }

        if ([sbEventName ContentsEqual: @"js_function_call" caseSensitive: bCaseSensitive] == YES) {
            //  (a) The model is requesting a tool call.  sbDelta holds the function-call JSON.
            //  StreamingJsToolCall runs the tool -- routing MCP tools to the server -- and appends the
            //  result to the transcript.  It must be called before this turn's null_terminator.
            NSLog(@"%@",@"[tool call requested]");
            NSLog(@"%@",[sbDelta GetAsString]);
            success = [ai StreamingJsToolCall: sbDelta];
            if (success == NO) {
                NSLog(@"%@",ai.LastErrorText);
                return;
            }

            bToolCallPending = YES;
        }
        else {
            if ([sbEventName ContentsEqual: @"null_terminator" caseSensitive: bCaseSensitive] == YES) {
                //  (c) This streamed turn has finished.
                if (bToolCallPending == YES) {
                    //  Continue the conversation so the model can use the tool result.  No new
                    //  InputAddText -- the tool result is already in the transcript.
                    bToolCallPending = NO;
                    success = [ai Ask: @"text"];
                    if (success == NO) {
                        NSLog(@"%@",ai.LastErrorText);
                        return;
                    }

                }
                else {
                    bConversationDone = YES;
                }

            }
            else {
                //  (b) An "empty" event reports nothing this poll.  (d) Any other event is a normal
                //  streamed text delta, which we display and accumulate.
                if ([sbEventName ContentsEqual: @"empty" caseSensitive: bCaseSensitive] != YES) {
                    NSLog(@"%@%@%@%@",@"Event: ",[sbEventName GetAsString],@"  Delta: ",[sbDelta GetAsString]);
                    [sbFullResponse AppendSb: sbDelta];
                }

            }

        }

    }

}

NSLog(@"%@",@"Final streamed response:");
NSLog(@"%@",[sbFullResponse GetAsString]);
NSLog(@"%@",@"----");

//  (Optional) The full transcript, including the tool call and its result.
CkoJsonObject *convoJson = [[CkoJsonObject alloc] init];
convoJson.EmitCompact = NO;
success = [ai ExportConvo: @"test_conversation" json: convoJson];
if (success == NO) {
    NSLog(@"%@",ai.LastErrorText);
    return;
}

NSLog(@"%@",@"Full Conversation:");
NSLog(@"%@",[convoJson Emit]);

//  5) Close the MCP session.
success = [mcp Close];
if (success == NO) {
    NSLog(@"%@",mcp.LastErrorText);
    return;
}