GPT-5 MCP Server

continue_conversation

Resume an existing GPT-5 conversation by sending a new message with the conversation ID. Manage token limits and budget controls for continued interactions.

Instructions

Continue an existing conversation with GPT-5

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "conversation_id": "<conversation_id>",
      "message": "<message>"
    },
    "name": "continue_conversation"
  }
}

Input Schema

Name	Required	Description
`stream`	No	Enable streaming mode (server aggregates, client still returns final text)
`message`	Yes	The message to send in the conversation
`max_tokens`	No	Optional cap for this single response
`budget_limit`	No	Set or override per-conversation budget in USD
`conversation_id`	Yes	The ID of the conversation to continue
`confirm_spending`	No	User confirmation to proceed with spending if budget is tight

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 2, 2026

TDQS

B3/5.0

Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure, but it offers none. It does not mention spending, side effects, streaming behavior, budget limits, or confirmation requirements, all of which are significant for a tool involving monetary costs and conversation state changes. The description is purely a functional statement with no transparency about how the tool behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, focused sentence with no wasted words, front-loading the core purpose effectively. However, it is extremely sparse, which slightly undercuts its value as a complete tool description, but for conciseness alone it earns a strong score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 6 parameters including financial ones (budget_limit, confirm_spending), a streaming flag, and a token cap, yet the description provides no context about return values, cost implications, required confirmations, or streaming behavior. With no output schema and no annotations, this description is severely incomplete for a tool of this complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema provides 100% coverage of parameter descriptions, so the schema alone adequately documents the parameters. The tool description adds no additional meaning or context beyond the schema, leaving the agent to rely solely on schema descriptions. Per the rubric, baseline 3 is appropriate since schema coverage is high and no extra semantics are provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Continue an existing conversation with GPT-5' uses a specific verb (continue) and resource (existing conversation with GPT-5), clearly distinguishing it from sibling tools like start_conversation. It immediately conveys the tool's core action without ambiguity, making it stand out among similar conversational tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage: use this tool to continue an existing conversation rather than start a new one (contrasting with start_conversation). However, it does not explicitly state when to use this tool over alternatives like consult_gpt5 or summarize_conversation, nor does it mention any exclusions or prerequisites. The context is clear but minimal.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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