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flowscan-mcp

flowscan-mcp

by joshavenue
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Daily traders & new traders per builder

flowscan_builders_user_series
Read-only

Retrieve daily active and new trader time series across all builders or one builder, with configurable day range and metric selection.

Instructions

The /builders user-growth chart: daily count of active traders and new traders across all builders and per builder since 2025-07-27. Prefer this for daily active/new trader time series; for windowed totals use flowscan_builders_leaderboard (its new_users.7d is a separate dataset and can differ).

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": "flowscan_builders_user_series"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysNoMost recent N days (default 30).
fieldsNoPaths to keep, relative to `data` (list tools: each row); misses go to _fieldsNotFound.
metricNoDefault both.
builderNoBuilder id or address substring; omit for the aggregate series only.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations cover the safety profile (readOnlyHint, openWorldHint), and the description adds real behavioral context the annotations lack: the data begins 2025-07-27 and new_users.7d from the leaderboard is a separate dataset that can differ. It doesn't discuss pagination or return shape, keeping it just short of a 5.

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?

Two tightly written sentences, front-loaded with the core purpose and follow by the routing caveat and dataset caveat. Every clause carries information; no filler.

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

Completeness4/5

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

For a read-only time-series tool, the description supplies scope, start date, and a data-consistency caveat, which is enough to call it correctly even without an output schema. Return format details are the only thing not covered.

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 description coverage is 100%, so the schema already documents all four parameters with defaults and enums. The description implies the builder and time dimensions but adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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?

States a specific verb (daily count) and resource (active/new traders per builder), plus the scope (all builders and per builder) and start date. It clearly distinguishes itself from flowscan_builders_leaderboard without the agent needing to open either schema.

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

Usage Guidelines5/5

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

Explicitly says to prefer this for daily active/new trader time series and names the alternative (flowscan_builders_leaderboard) for windowed totals. Both the when-to-use and the routing condition are stated directly.

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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