Perplexity Web MCP

Overview Schema Source Related Servers Discussions Admin

pplx_glm52

Query the web with GLM 5.2, Z.ai's advanced model with thinking always enabled. Get AI-generated answers with source focus and optional conversation context via Perplexity Web MCP.

Instructions

GLM 5.2 — Z.ai's advanced model with thinking always enabled. COSTS 1 PRO SEARCH QUERY.

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": {
      "query": "<query>"
    },
    "name": "pplx_glm52"
  }
}

Input Schema

Name	Required	Default
`query`	Yes
`source_focus`	No	web
`conversation_id`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.14.0Jul 4, 2026

TDQS

C2.1/5.0

Behavior2/5

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

With no annotations, the description must fully explain behavior. It only notes 'thinking always enabled' and cost, omitting details like required permissions, side effects, response format, or error conditions. Insufficient for safe use.

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

Conciseness2/5

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

The description is extremely short but fails to convey essential information. Conciseness should not come at the expense of completeness; here it is under-specified.

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

Completeness2/5

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

Given the complexity (3 params, no annotations, output schema present), the description is far from complete. It lacks usage context, parameter explanations, and behavioral details, making it inadequate for proper tool invocation.

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

Parameters1/5

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

Schema coverage is 0%, and the description provides zero information about the three parameters (query, source_focus, conversation_id). The agent gets no help beyond the raw schema.

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

Purpose3/5

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

The description names the model (GLM 5.2) and mentions 'advanced model with thinking always enabled', but lacks a clear verb like 'query' or 'ask'. It implies the tool is for submitting queries to this model, but doesn't explicitly state the action, making it only somewhat clear.

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?

No guidance on when to use this tool versus siblings like pplx_ask, pplx_query, or pplx_smart_query. The only hint is the model name and cost, which is insufficient for selection.

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