agentweb-mcp

agent_history

Retrieve past business lookups and interactions to recall details without re-searching.

Instructions

Retrieve this agent's interaction history — every business it searched for, viewed, or contributed to. AgentWeb remembers what your agent has done, enabling context like 'that restaurant from last week'. History persists for 90 days, up to 500 interactions. Use this to recall past lookups without re-searching.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "agent_history"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No	Max entries to return (default: 50, max: 500)
`offset`	No	Skip N entries for pagination (default: 0)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.17.0Jun 21, 2026

TDQS

A4.1/5.0

Behavior4/5

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

No annotations provided, so description carries full burden. It discloses history retention (90 days, up to 500 interactions) and the scope of remembered actions. This adds useful behavioral context beyond schema.

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 concise, with two well-structured sentences. No wasted words; each sentence adds value.

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?

Despite no output schema, the description does not detail the return format or ordering. It implies a list of businesses but lacks specifics. Given low complexity, it is adequate but not fully complete.

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?

Schema coverage is 100%, so baseline is 3. The description does not add new meaning beyond the schema's parameter descriptions (limit with default and max, offset).

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 the tool retrieves the agent's interaction history, specifying the actions (searched, viewed, contributed) and enabling context like recalling past lookups. It distinguishes from siblings like agent_favorites.

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 gives a clear usage hint ('recall past lookups without re-searching') but does not explicitly state when not to use it or provide alternatives. The context is sufficient but lacks exclusion criteria.

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