Skip to main content
Glama

Server Details

Financial market intelligence — real-time stock quotes (Twelve Data), market indices (S&P 500, VIX, NASDAQ, gold, oil via FRED), and SEC 13F institutional holdings. First traditional market data API on x402.

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL

Glama MCP Gateway

Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.

MCP client
Glama
MCP server

Full call logging

Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.

Tool access control

Enable or disable individual tools per connector, so you decide what your agents can and cannot do.

Managed credentials

Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.

Usage analytics

See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.

100% free. Your data is private.
Tool DescriptionsA

Average 3.9/5 across 3 of 3 tools scored.

Server CoherenceA
Disambiguation5/5

Each tool targets a completely distinct data domain: institutional holdings, market indices, and stock quotes. There is no overlap or ambiguity in their purposes.

Naming Consistency5/5

All tool names follow a consistent 'get_' prefix followed by a descriptive noun phrase (institutional_holdings, market_indices, stock_quotes). The pattern is uniform and predictable.

Tool Count5/5

With only 3 tools, the server is tightly scoped and each tool provides a distinct, valuable capability for market data retrieval. This is well within the typical 3-15 range and feels appropriate for a focused utility.

Completeness4/5

The tool surface covers key market data needs, but lacks historical price data or company fundamentals, which are common adjacent use cases. These are minor gaps that agents can work around by combining the existing tools or using external data.

Available Tools

3 tools
get_institutional_holdingsAInspect

Get institutional investor 13F SEC filings for a given CIK or institution name. Default is Berkshire Hathaway (CIK 0001067983).

ParametersJSON Schema
NameRequiredDescriptionDefault
cikNoSEC CIK number (e.g. 0001067983 for Berkshire Hathaway)0001067983
institutionNoInstitution name to search for CIK (e.g. "Bridgewater Associates")
Behavior3/5

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

With no annotations, the description carries the burden of disclosing behavior. It discloses the read-only nature ('Get'), the selection mechanism (CIK or institution name), and a default value. However, it does not mention what happens if both parameters are provided, the return format, or any access limitations, so transparency is moderate. Score 3.

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 concise sentence with a second clarifying sentence about the default. It is front-loaded with the action and resource, with no filler. Score 5.

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 simple getter with two optional parameters, the description provides enough context for an agent to understand the tool's function. Since there is no output schema, the description does not explain the return structure, but that is acceptable for a straightforward data retrieval tool. Score 4.

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?

The input schema already describes both parameters fully, including a default for cik, so schema coverage is 100%. The description adds minimal semantic value beyond repeating that the tool accepts CIK or institution name. Baseline of 3 is appropriate.

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

Purpose4/5

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

The description uses a specific verb 'Get' and clearly identifies the resource 'institutional investor 13F SEC filings'. It specifies the key parameters (CIK or institution name) and includes a default, making the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like get_market_indices, so a score of 4 is appropriate.

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 implies the tool is used to retrieve 13F filings for a given CIK or institution, which provides clear context. However, it does not state when to prefer this tool over siblings or mention any exclusions or alternatives, so it lacks explicit usage guidance. Thus a score of 3.

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

get_market_indicesAInspect

Get major market indices and macro indicators: S&P 500, NASDAQ, VIX, 10-Year Treasury, WTI Oil, Gold, USD/EUR. Data from FRED (St. Louis Fed).

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Behavior3/5

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

With no annotations provided, the description carries full behavioral disclosure burden. It adds value by naming the data source (FRED), but it does not mention response format, update frequency, rate limits, or any other traits. The simple getter nature is clear, but additional context would be beneficial.

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 two sentences, front-loaded with the purpose and then the source. Every word earns its place, delivering maximum information in minimal space.

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 zero-parameter retrieval tool with no output schema, the description is sufficiently complete: it lists all expected data items and the source. It could optionally note whether data is real-time or delayed, but that is not critical for basic usage.

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

Parameters4/5

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

The tool has zero parameters, so the schema imposes no burden. The description compensates by listing the specific indicators returned, giving the agent a clear idea of what the output covers. Baseline for 0 params is 4, and the description meets it.

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's purpose with a specific verb ('Get') and explicitly lists the resources (S&P 500, NASDAQ, VIX, etc.). This distinguishes it from siblings like get_stock_quotes (individual stock prices) and get_institutional_holdings (holdings data).

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 implies its use case by enumerating macro indicators and indices, which differentiates it from stock-specific queries. However, it does not explicitly state when to use this tool versus alternatives or provide any exclusion criteria.

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

get_stock_quotesAInspect

Get real-time stock price quotes for one or more symbols. Returns price, % change, 52-week high/low, exchange, and currency.

ParametersJSON Schema
NameRequiredDescriptionDefault
symbolsNoComma-separated ticker symbols (e.g. AAPL,MSFT,NVDA)AAPL,MSFT,NVDA,GOOGL,TSLA
exchangeNoFilter by exchange: NYSE or NASDAQ
Behavior3/5

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

With no annotations, the description must convey the tool's behavioral profile. It discloses the returned data (price, % change, 52-week high/low, exchange, currency) but omits potential error behavior, rate limits, or data source reliability. For a read-only quote tool, this is adequate but not comprehensive.

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 highly concise, consisting of two sentences that immediately state the core function and return fields. There is no filler or redundant information.

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?

Given the tool's simplicity, the absence of an output schema, and the description's listing of return fields, it provides sufficient context. It could be more explicit about the response structure (e.g., array of objects) or handling of multiple symbols, but it is reasonably complete for a quote retrieval tool.

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?

The input schema already provides full descriptions and defaults for both parameters (100% coverage). The description adds little beyond confirming that one or more symbols are supported, which aligns with the 'symbols' parameter. No deeper parameter semantics are provided.

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 uses a specific verb ('Get') and clearly identifies the resource ('real-time stock price quotes') for one or more symbols. It also lists return fields, which distinguishes it from sibling tools for holdings and indices.

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 clearly implies when to use the tool: whenever real-time stock quotes are needed. However, it doesn't explicitly mention alternatives or exclusions, though the sibling tool names make the differentiation obvious.

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

Discussions

No comments yet. Be the first to start the discussion!

Related MCP Servers

  • A
    license
    A
    quality
    A
    maintenance
    GTM signal intelligence suite for AI agents. Six tools: hiring signals, tech stack detection, company-to-LinkedIn resolution, ICP scoring, job board scanning, and a combined signals aggregator. Built for outbound sales workflows.
    11
    737
    1
    MIT
  • F
    license
    -
    quality
    C
    maintenance
    Browse IndustryLens's published competitive-intelligence reports and head-to-head competitor comparisons from any AI agent — real, source-backed data.

View all MCP Servers

Try in Browser

Your Connectors

Sign in to create a connector for this server.

Resources