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mcp-server

by io.github.forcedreamai

Get a live market quote

forcedream_market_quote
Read-only

Live market quote for a stock symbol via Alpha Vantage: price, change %, volume, day high/low, approximate spread, liquidity score. Hard-cached. WORM-sealed. Requires authentication.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYesTicker symbol, e.g. "AAPL", "IBM".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
priceYes
symbolYes
volumeNo
day_lowNo
day_highNo
worm_sealNo
change_percentNo
liquidity_scoreNo

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true and openWorldHint=true. The description adds valuable behavioral context: hard-cached, WORM-sealed (immutable), and requires authentication. This goes beyond the annotations and helps the agent understand caching, data permanence, and auth requirements.

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 a single sentence that packs all essential information: purpose, data source, output fields, and key attributes (cached, sealed, auth). No filler words; every clause adds value. Front-loaded with the core purpose.

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's low complexity (1 parameter) and presence of an output schema, the description covers all necessary context: data source (Alpha Vantage), output fields, caching behavior, immutability (WORM-sealed), and authentication needs. It does not need to explain return values since an output schema exists.

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% with one parameter 'symbol' well-described in the schema. The description does not add further details about the parameter (e.g., accepted formats, case sensitivity) beyond the schema, so it meets the baseline for high coverage.

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 title 'Get a live market quote' and description clearly state the verb (get) and resource (live market quote). It lists specific data fields: price, change %, volume, day high/low, approximate spread, liquidity score. No sibling tool has a similar purpose, so differentiation is not needed.

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

Usage Guidelines3/5

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

The description does not explicitly state when to use this tool versus alternatives. It implies use for market data but lacks explicit guidance on when not to use it (e.g., for historical data) or mention of alternative tools. The phrase 'hard-cached' hints at data freshness, but no clear usage context is provided.

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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TDQS

A4/5.0
Disambiguation3/5

Most tools have clearly distinct purposes (fraud vs extract vs generate vs sentiment vs lead scoring vs quote vs proof verification). However, there is notable overlap among the search_* discovery tools: forcedream_search_agents, forcedream_search_reliability, and forcedream_search_costs all surface overlapping agent metadata (success_rate appears in both search_agents and search_reliability), which could cause misselection. Additionally, forcedream_extract_data vs forcedream_extract_entities vs forcedream_extract_action_items overlap somewhat in the extraction domain despite distinct outputs (JSON fields vs raw entities vs action items).

Naming Consistency4/5

The forcedream_ prefix is used consistently throughout, and most tools follow a forcedream_<verb>_<object> pattern (extract_data, generate_code, score_lead, security_scan). However, there is inconsistency in verb style: check vs extract vs generate vs invoke vs search vs verify vs summarize are all different verb types, and the objects don't follow a uniform noun convention (some are actions like invole_agent, others resources like market_quote). The naming is readable and discoverable but not perfectly uniform.

Tool Count4/5

At 17 tools, this is slightly above the ideal range but justifiable given the broad multi-service scope (fraud, extraction, generation, discovery, verification). Each tool maps to a reasonably distinct service capability, and none feel like padding. The count borders on heavy but earns its place given the diverse domain coverage.

Completeness4/5

The tool surface is comprehensive for a multi-purpose AI/ML service platform, covering fraud detection, data extraction, code generation, sentiment analysis, embeddings, lead scoring, security scanning, summarization, market quotes, agent discovery, and proof verification. Missing are update/delete operations, but this appears to be a stateless service rather than a CRUD resource store. The discovery tools (search_* variants) and meta capabilities (verify_proof) round out the lifecycle well, though there's no clear cleanup or batch-processing tool.

Resources