Skip to main content
Glama

patternfetch

by io.github.MarvinRey7879

Multi-Timeframe Brief

patternfetch_multi
Read-onlyIdempotent

Get a multi-timeframe market-state view for one stock, ETF, or crypto ticker in a single call: a token-compact brief for each requested timeframe (default 1h, 4h, 1d) PLUS a cross-timeframe alignment read — whether the trends across timeframes agree or diverge, with the split spelled out (e.g. "1h up / 4h up / 1d down"). WHEN: an agent wants to know if a setup is confirmed across horizons or conflicting between them, without making 3 separate brief calls. WHEN NOT: you only care about one timeframe (use brief). The alignment/divergence is impersonal DESCRIPTIVE data, not a signal to act on. Example: {"ticker":"BTC/USDT","timeframes":["1h","4h","1d"]}. Not investment advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many recent bars to analyse: integer >= 20, capped at 1000, default 200. Fewer bars = fewer tokens.
marketNoOptional asset-class override. Omit and it is inferred from the ticker: a "BASE/QUOTE" pair is crypto, a plain symbol is a US stock/ETF.
tickerYesSymbol to analyse. US stock or ETF like "AAPL" / "SPY", or a crypto spot pair like "BTC/USDT". Always spell crypto as a pair: a bare "BTC" or "ETH" is a real US-listed ETF, NOT the coin, and it will return that ETF's prices without failing. Affected responses carry a "notice" field.
timeframesNoBar sizes to compare, at most 4, e.g. ["1h","4h","1d"]. Defaults to ["1h","4h","1d"] when omitted.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedInput schema / properties / ticker / description
      Previous value: -"Symbol to analyse. US stock or ETF like \"AAPL\" / \"SPY\", or a crypto spot pair like \"BTC/USDT\"."New value: +"Symbol to analyse. US stock or ETF like \"AAPL\" / \"SPY\", or a crypto spot pair like \"BTC/USDT\". Always spell crypto as a pair: a bare \"BTC\" or \"ETH\" is a real US-listed ETF, NOT the coin, and it will return that ETF's prices without failing. Affected responses carry a \"notice\" field."
  2. Changed4 schema fields changed
    • addedInput schema / properties / limit / description
      Added value: +"How many recent bars to analyse: integer >= 20, capped at 1000, default 200. Fewer bars = fewer tokens."
    • addedInput schema / properties / market / description
      Added value: +"Optional asset-class override. Omit and it is inferred from the ticker: a \"BASE/QUOTE\" pair is crypto, a plain symbol is a US stock/ETF."
    • addedInput schema / properties / ticker / description
      Added value: +"Symbol to analyse. US stock or ETF like \"AAPL\" / \"SPY\", or a crypto spot pair like \"BTC/USDT\"."
    • addedInput schema / properties / timeframes / description
      Added value: +"Bar sizes to compare, at most 4, e.g. [\"1h\",\"4h\",\"1d\"]. Defaults to [\"1h\",\"4h\",\"1d\"] when omitted."
  3. Changed1 schema field changed
    • addedInput schema / properties / market
      Added value: +{
+  "enum": [
+    "crypto",
+    "stock"
+  ],
+  "type": "string"
+}
  4. Added

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds that the alignment/divergence is 'impersonal DESCRIPTIVE data, not a signal to act on' and includes 'Not investment advice.' This provides additional behavioral context beyond the annotations.

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

Conciseness4/5

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

The description is well-structured with clear sections (WHEN, WHEN NOT) and includes an example. While it is a bit lengthy, every sentence serves a purpose. Minor redundancy could be trimmed, but overall it is efficient.

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

Completeness5/5

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

Given the tool has 4 parameters, no output schema, and moderate complexity, the description is thorough. It explains the return content (briefs per timeframe plus alignment read), provides defaults, constraints (max 4 timeframes), and handles edge cases (crypto vs ETF). This enables an agent to use the tool correctly without additional assumptions.

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

Parameters5/5

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

Schema description coverage is 100%. The description adds valuable information beyond the schema: it clarifies that bare crypto symbols like 'BTC' are treated as US-listed ETFs and that a 'notice' field is included in such cases. It also specifies default timeframes and that at most 4 timeframes are allowed.

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 verb 'Get' and the resource 'multi-timeframe market-state view'. It specifies that the result includes a brief for each requested timeframe and a cross-timeframe alignment read. It distinguishes itself from siblings by noting that it avoids making three separate brief calls.

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?

The description explicitly includes WHEN and WHEN NOT sections. WHEN states: 'an agent wants to know if a setup is confirmed across horizons or conflicting between them, without making 3 separate brief calls.' WHEN NOT states: 'you only care about one timeframe (use brief).' This provides clear guidance and names the alternative sibling tool.

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

All patternfetch toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.7/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: analogs for historical patterns, brief for current state, capabilities for metadata, delta for changes, multi for multi-timeframe, scan for screening. No overlap in functionality.

Naming Consistency5/5

All tools follow a consistent 'patternfetch_<noun>' pattern using snake_case, making it predictable. No mixed conventions or ambiguous verbs.

Tool Count5/5

6 tools is well-scoped for a technical analysis server. Each tool earns its place, covering key operations without being excessive or insufficient.

Completeness4/5

The tool set covers core workflows: current state, multi-timeframe, scanning, historical analogs, and polling for changes. Minor gaps (e.g., no raw data endpoint) are acceptable given the server's focus on processed insights.

Resources