Skip to main content
Glama
gamesme

chatlab-mcp

by gamesme

get_full_conversation

Retrieve the complete conversation history across multiple pages in a compact text format. Useful for analyzing small to medium chat sessions.

Instructions

Get full conversation across multiple pages, returns compact text format. Use for small to medium sessions only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idYesSession ID
max_total_messagesNoMaximum total messages to retrieve (default: 500)
merge_consecutiveNoMerge consecutive messages from same sender (default: true)
filter_invalidNoFilter meaningless messages (default: true)
Behavior3/5

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

No annotations are provided, so the description must carry the burden. It mentions 'compact text format' and 'across multiple pages', indicating pagination handling and output type. However, it lacks details on performance implications, rate limits, or whether the operation is read-only, which is a gap.

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 two sentences with no redundant information. It efficiently conveys the core function and usage scope, earning its place.

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?

Given no output schema, the description partially compensates by stating the return format is 'compact text format'. However, it does not detail that format or mention automatic pagination, leaving gaps for a tool with 4 parameters. It is adequate but not thorough.

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?

With 100% schema description coverage, the schema already documents all parameters. The description adds no further semantic value beyond the schema, 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 clearly states 'Get full conversation across multiple pages' with a specific verb and resource, and mentions the output format 'compact text format'. It also distinguishes usage scope with 'Use for small to medium sessions only', differentiating it from siblings like get_messages or get_conversation_between.

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

Usage Guidelines4/5

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

The description provides a clear usage recommendation ('Use for small to medium sessions only') but does not explicitly mention when not to use it or suggest alternative tools for large sessions. This leaves some ambiguity.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/gamesme/chatlab-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server