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Glama

Server Details

One command to validate, transform, and deduplicate — chain GoldenCheck + Flow + Match.

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL
Repository
benzsevern/goldenpipe
GitHub Stars
0

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 DescriptionsC

Average 2.5/5 across 4 of 4 tools scored.

Server CoherenceA
Disambiguation5/5

Each tool has a clearly distinct purpose: explain_pipeline describes configs, list_stages enumerates stages, run_pipeline executes pipelines, and validate_pipeline checks wiring. There is no overlap in functionality, making tool selection unambiguous for an agent.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (explain_pipeline, list_stages, run_pipeline, validate_pipeline) with snake_case throughout. This predictable naming convention enhances readability and usability.

Tool Count5/5

With 4 tools, the server is well-scoped for pipeline management, covering explanation, listing, execution, and validation. Each tool earns its place without redundancy, making the count appropriate for the domain.

Completeness4/5

The tools provide solid coverage for core pipeline operations, but minor gaps exist, such as missing tools for creating, updating, or deleting pipeline configs. Agents can likely work around this by using external methods, but it's not a complete CRUD lifecycle.

Available Tools

4 tools
explain_pipelineCInspect

Explain what a pipeline config does

ParametersJSON Schema
NameRequiredDescriptionDefault
config_pathYes
Behavior2/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. While 'explain' implies a read-only operation, the description does not confirm this, nor does it disclose output format, side effects, file system access, or whether the explanation includes nested dependencies.

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

Conciseness3/5

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

The description is brief (6 words) and contains no filler, but given the complete lack of schema documentation and annotations, this brevity results in under-specification rather than efficient communication.

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

Completeness2/5

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

Inadequate for even a single-parameter tool. With no output schema provided, the description should explain what form the explanation takes (string, object, markdown). It leaves critical gaps that would prevent an agent from confidently invoking the tool.

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

Parameters2/5

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

With 0% schema description coverage, the description must compensate for the undocumented 'config_path' parameter. It loosely implies the parameter refers to a 'pipeline config' but fails to specify that it is a file path, required format, or whether it supports relative/absolute paths.

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

Purpose3/5

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

States the verb (explain) and resource (pipeline config), establishing the basic domain. However, it remains vague about the nature of the explanation (e.g., human-readable summary, technical breakdown, validation report) and does not differentiate from sibling tools like 'validate_pipeline' or 'list_stages'.

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

Usage Guidelines2/5

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

Provides no guidance on when to use this tool versus 'run_pipeline', 'validate_pipeline', or 'list_stages'. No prerequisites, constraints, or workflow context is mentioned.

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

list_stagesBInspect

List all discovered pipeline stages

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Behavior2/5

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

No annotations provided, so description carries full burden. It fails to disclose read-only nature, what 'discovered' means (runtime detection vs static config), or return format despite missing output schema.

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?

Single sentence is efficiently structured and front-loaded. However, given lack of annotations and output schema, the extreme brevity constitutes under-specification rather than optimal conciseness.

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

Completeness2/5

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

With no annotations, no output schema, and 0 parameters, the description must explain what constitutes a stage and the return value. It omits this critical context, leaving agents uncertain about tool utility.

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?

Input schema contains 0 parameters. Baseline score applies as there are no parameters requiring semantic clarification in the description.

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?

Uses specific verb 'List' and resource 'pipeline stages', clearly distinguishing from siblings (explain_pipeline, run_pipeline, validate_pipeline) by action type. However, the scope 'discovered' is undefined and could confuse.

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

Usage Guidelines2/5

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

Provides no guidance on when to use this versus explain_pipeline (which also inspects pipeline state) or prerequisites for listing stages. No alternatives or exclusions mentioned.

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

run_pipelineCInspect

Run a pipeline on a file

ParametersJSON Schema
NameRequiredDescriptionDefault
sourceYes
config_pathNo
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure, but it fails to explain what 'running' entails. It doesn't indicate whether this creates output artifacts, modifies the source data, requires specific permissions, or has side effects like resource consumption or billing implications.

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

Conciseness3/5

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

The description is extremely brief (5 words) and front-loaded with the action verb. However, the brevity reflects under-specification rather than efficient communication; for a complex operation like pipeline execution, additional context is needed to make the description useful.

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

Completeness2/5

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

Given the complexity of pipeline execution, the presence of related sibling tools, 0% schema coverage, and no output schema or annotations, the description is inadequate. It fails to address error handling, return values, or the relationship between input parameters and pipeline behavior.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate significantly. The phrase 'on a file' weakly hints that 'source' might be a file path, but this is speculative. The optional 'config_path' parameter is completely undocumented, and there's no explanation of parameter formats, valid values, or relationships between parameters.

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

Purpose3/5

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

The description provides a basic verb ('Run') and resource ('pipeline'), distinguishing it from siblings like 'explain_pipeline' or 'validate_pipeline'. However, the phrase 'on a file' is ambiguous—it doesn't clearly map to the 'source' parameter and ignores the 'config_path' parameter entirely, leaving the exact scope undefined.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus siblings like 'validate_pipeline' (which might be a prerequisite) or 'explain_pipeline'. There are no prerequisites, warnings, or alternative suggestions mentioned.

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

validate_pipelineCInspect

Validate pipeline wiring

ParametersJSON Schema
NameRequiredDescriptionDefault
stagesYes
pipelineYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden, yet it fails to disclose whether this is read-only, what validation rules are applied, or what the return format is (boolean, error list, etc.). The term 'wiring' hints at stage connectivity but remains undefined.

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

Conciseness2/5

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

While brief (three words), this is under-specification rather than efficient conciseness. Given the lack of schema documentation and annotations, the description needs to front-load critical details rather than remain this terse.

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

Completeness2/5

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

For a validation tool with 2 required parameters and no output schema or annotations, the description is inadequate. It should explain what constitutes valid vs. invalid wiring and what validation errors might be returned.

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

Parameters1/5

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

With 0% schema description coverage, the description completely fails to compensate. It mentions neither the 'pipeline' parameter (is it an ID? name? config?) nor the 'stages' array (expected format? existing vs. new stages?).

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

Purpose3/5

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

The description states the verb (validate) and resource (pipeline wiring), but 'wiring' is jargon without explanation. It distinguishes from siblings (run_pipeline, explain_pipeline) by using 'validate' but doesn't clarify what aspect of the pipeline is being validated.

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

Usage Guidelines2/5

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

No guidance provided on when to use this versus run_pipeline or explain_pipeline. No mention of prerequisites (e.g., whether pipeline must exist first) or what to do with validation results.

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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