Skip to main content
Glama
bradcstevens

Copilot Studio Agent Direct Line MCP Server

by bradcstevens

get_conversation_history

Retrieve message history for a specific conversation to review previous interactions and maintain context.

Instructions

Retrieve message history for a conversation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
conversationIdYesConversation ID
limitNoMaximum number of messages to return

Implementation Reference

  • The primary handler function for the 'get_conversation_history' tool. Validates input using the schema, checks user permissions, retrieves conversation state from the manager, slices history if limit provided, formats messages, logs audit, and returns structured response.
    private async handleGetConversationHistory(
      args: Record<string, unknown>,
      userContext?: UserContext
    ) {
      const { conversationId, limit } = validateToolArgs(GetConversationHistoryArgsSchema, args);
    
      // Validate permissions if user context exists
      if (userContext) {
        this.validateUserConversationAccess(userContext.userId, conversationId);
      }
    
      try {
        const convState = this.conversationManager.getConversation(conversationId);
        if (!convState) {
          throw new Error(`Conversation ${conversationId} not found or expired`);
        }
    
        let history = convState.messageHistory;
    
        if (limit && limit > 0) {
          history = history.slice(-limit);
        }
    
        const formattedHistory = history.map((activity) => ({
          id: activity.id,
          type: activity.type,
          timestamp: activity.timestamp,
          from: activity.from,
          text: activity.text,
          attachments: activity.attachments,
        }));
    
        // Audit log
        this.logAudit({
          timestamp: Date.now(),
          userId: userContext?.userId,
          action: 'get_conversation_history',
          conversationId,
          details: { messageCount: formattedHistory.length },
        });
    
        return createSuccessResponse({
          conversationId,
          messageCount: formattedHistory.length,
          totalMessages: convState.messageHistory.length,
          messages: formattedHistory,
        });
      } catch (error) {
        throw new Error(
          `Failed to get conversation history: ${error instanceof Error ? error.message : String(error)}`
        );
      }
    }
  • Zod schema defining input arguments for the tool: required conversationId string and optional positive integer limit. Used for validation in the handler.
    /**
     * Schema for get_conversation_history tool arguments
     */
    export const GetConversationHistoryArgsSchema = z.object({
      conversationId: z.string().min(1, 'Conversation ID is required'),
      limit: z.number().int().positive().optional(),
    });
    
    export type GetConversationHistoryArgs = z.infer<typeof GetConversationHistoryArgsSchema>;
  • Tool registration in the ListToolsRequestSchema handler for stdio transport, providing name, description, and JSON input schema.
    {
      name: 'get_conversation_history',
      description: 'Retrieve message history for a conversation',
      inputSchema: {
        type: 'object',
        properties: {
          conversationId: {
            type: 'string',
            description: 'Conversation ID',
          },
          limit: {
            type: 'number',
            description: 'Maximum number of messages to return',
          },
        },
        required: ['conversationId'],
      },
    },
  • Tool registration in the HTTP 'tools/list' handler, providing name, description, and JSON input schema.
    {
      name: 'get_conversation_history',
      description: 'Retrieve message history for a conversation',
      inputSchema: {
        type: 'object',
        properties: {
          conversationId: {
            type: 'string',
            description: 'Conversation ID',
          },
          limit: {
            type: 'number',
            description: 'Maximum number of messages to return',
          },
        },
        required: ['conversationId'],
      },
    },

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior2/5

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. It only says 'Retrieve message history' and does not explicitly confirm read-only behavior, mention pagination, ordering, error handling, or authentication requirements. The verb 'retrieve' implies a read operation, but this is not stated.

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

Conciseness5/5

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

The description is a single, well-formed sentence that conveys the core purpose without any superfluous words. It is front-loaded and every word contributes meaning.

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

Completeness3/5

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

The tool is simple (two parameters, no output schema, no annotations), and the schema covers parameters adequately. However, the description lacks context about response format, message ordering, or usage scenarios, making it minimally viable but not comprehensive.

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 already documents both parameters with clear descriptions ('Conversation ID' and 'Maximum number of messages to return'), achieving 100% schema coverage. The tool description adds no further parameter semantics, so a baseline score of 3 is appropriate.

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 uses a specific verb 'Retrieve' and clearly identifies the resource as 'message history for a conversation.' This distinguishes it from sibling tools like send_message, start_conversation, and end_conversation, which perform different actions on conversations.

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

Usage Guidelines2/5

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

The description offers no guidance on when to use this tool versus alternatives. It simply states the action without mentioning context or exclusions, and sibling tools are not referenced, leaving the agent to infer usage solely from the name.

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