Skip to main content
Glama

FlowVolt

by io.github.Larshiensch99
OverviewDiscussionsAdmin

Server Details

Cold engine for B2B founders. Detects buying signals, drafts outreach, books qualified meetings.

Glama couldn't complete the latest health check. If this server requires authentication, missing or expired test credentials may be the cause. A test profile lets Glama authenticate for health checks and discover tools; it is separate from your personal connections.

If you are the author, claim ownership, then add or update a test profile under Admin → Test Profile.

Status
Unhealthy
Uptime
29.0% over 38 days
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL

TDQS

A3.8/5.0

Scored across 3 tools

Disambiguation5/5

Each tool performs a completely distinct function—numeric addition, text echoing, and time retrieval—with zero overlap in purpose. An agent would never confuse these tools.

Naming Consistency3/5

add and echo are single-word verbs, while server_time is a noun phrase with an underscore, creating a slight inconsistency. The names are readable and lowercase, but the pattern is not uniformly maintained.

Tool Count3/5

Three tools falls within the acceptable range, but the tools are so unrelated that the set feels like a random collection rather than a purposeful server. A more focused server would either have more tools around a coherent domain or make a clearer case for each tool.

Completeness2/5

There is no identifiable domain or workflow to assess coverage against; the tools are disconnected and provide only trivial operations. As a usable server for any real task, it offers almost no meaningful capability surface.

Available Tools

3 tools
addAddAInspect

Adds two numbers and returns the sum.

ParametersJSON Schema
NameRequiredDescriptionDefault
aYes
bYes

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations available, the description carries the full burden of behavioral disclosure. It fully describes the operation (adding two numbers) and the return value (the sum), leaving no room for hidden side effects, state changes, or other behaviors. For a pure arithmetic function, this is complete transparency.

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, efficient sentence with no redundant words. The core operation and return value are front-loaded, and there is no filler or repetition.

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?

For a tool with two numeric parameters, no annotations, no output schema, and a trivial operation, the description provides all necessary context: what the inputs are, what the tool does, and what the caller receives. Nothing an agent needs to invoke it correctly is missing.

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 input schema only provides names and types (a, b as numbers), with 0% description coverage. The description compensates by clarifying that both parameters are the two addends and that the result is their sum, which gives functional meaning beyond the raw schema. It could only be improved by explicitly naming the parameters.

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 states a specific verb ('Adds'), the resource ('two numbers'), and the outcome ('returns the sum'). It is not a tautology of the name and clearly distinguishes this tool from the sibling tools echo and server_time.

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 implies the clear context: use this tool when you need to add two numbers and get their sum. While it doesn't explicitly exclude siblings, none of them perform arithmetic, so the context is unambiguous and no exclusions are needed.

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

echoEchoAInspect

Echoes the provided text back to the caller.

ParametersJSON Schema
NameRequiredDescriptionDefault
textYesText to echo back

TDQS

A4.1/5.0
Behavior4/5

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

No annotations exist, so the description carries the full burden. It clearly conveys the core behavior and result, implying no state change. However, it does not explicitly address formatting, length limits, or edge cases, leaving a minor transparency gap.

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?

A single sentence front-loads the action and result with zero filler. Every word contributes to understanding the tool.

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?

For a one-parameter echo tool with no output schema, the description fully suffices: it tells the agent what the tool does and what it returns. No additional context is necessary.

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 documents the single 'text' parameter with 100% coverage. The description adds no meaning beyond what the schema provides, so 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 ('Echoes'), a resource ('the provided text'), and a destination ('back to the caller'). Clearly distinguishable from sibling tools add and server_time.

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 for repeating text back, but it offers no explicit when-to-use guidance, alternatives, or exclusions. For a trivial tool the context is self-evident, but no direct usage guidance is provided.

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

server_timeServer timeAInspect

Returns the current server time (ISO 8601, UTC).

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It adequately conveys that this is a read-only retrieval operation ('returns') and specifies the output format and timezone (ISO 8601, UTC), which is valuable behavioral context.

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?

A single, front-loaded sentence provides complete information without any filler. Every word earns its place.

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?

For a zero-parameter utility with no output schema, the description is fully sufficient: it states what the tool returns and the exact format of that return value. No additional context is needed for an agent to call it correctly.

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 and the schema is empty, so there are no parameter semantics to document. The description appropriately confirms that calling the tool requires no inputs.

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 states a specific verb and resource: it returns the current server time in ISO 8601 UTC format. This clearly distinguishes it from siblings add and echo, which perform unrelated operations.

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 makes the intended use clear: call this tool whenever the current server time is needed. There are no time-related sibling tools requiring exclusions, so no explicit alternative guidance is necessary.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 26 tool updates
    • Addedadd
    • Removedbook_meeting
    • Removedcalculate_payback
    • Removeddiscover_business
    • Addedecho
    • Removededit_message
    • Removedenqueue_lead
    • Removedfind_leads
    • Removedflowvolt_freetrial
    • Removedflowvolt_send_trial
    • Removedget_funnel
    • Removedget_pipeline
    • Removedget_receipts
    • Removedget_replies
    • Removedget_started
    • Removedget_subscription_status
    • Removedlist_meetings
    • Removedmanage_billing
    • Removedpause_engine
    • Removedpreview_message
    • Removedquote
    • Removedresume_engine
    • Removedsearch_people
    • Addedserver_time
    • Removedset_goal
    • Removedsubscribe
  2. 2 tool updates
    • Addedflowvolt_freetrial
    • Addedflowvolt_send_trial
  3. 12 tool updates
    • Addedcalculate_payback
    • Addeddiscover_business
    • Addededit_message
    • Changedfind_leads2 fields changed
      • changedInput schema / properties / email / description
        Previous value: -"Optional. The user's work email — if provided on a free_trial call, we create a provisional tenant and mail them a follow-up. Without it, free_trial still works but no follow-up email."New value: +"Optional. The user's work email."
      • changedInput schema / properties / quote_id / description
        Previous value: -"A quote_id returned by the quote() tool. Must be a free_trial or topup plan. Example: 'q_trial_abc12345'"New value: +"A quote_id returned by quote() or discover_business(). Must be free_trial or topup."
    • Changedget_started3 fields changed
      • addedInput schema / properties / company
        Added value: +{
+  "description": "The user's business name if known. Optional.",
+  "type": "string"
+}
      • removedInput schema / properties / context
        Removed value: -{
-  "description": "Anything the user mentioned about their company, role, or what they're trying to do. Example: 'I run a B2B SaaS in Holland selling to fintechs.' Optional but improves the response.",
-  "type": "string"
-}
      • addedInput schema / properties / name
        Added value: +{
+  "description": "The user's first name if known. Optional.",
+  "type": "string"
+}
    • Changedget_subscription_status2 fields changed
      • changedInput schema / properties / email / description
        Previous value: -"Optional. The email used at Stripe Checkout. Only needed if you're not authenticated with an MCP token."New value: +"Stripe Checkout email if not authenticated."
      • addedInput schema / properties / name
        Added value: +{
+  "description": "User's first name if known.",
+  "type": "string"
+}
    • Changedmanage_billing2 fields changed
      • changedInput schema / properties / email / description
        Previous value: -"Optional. The email used at Stripe Checkout. Only needed if you're not authenticated with an MCP token."New value: +"Stripe Checkout email if not authenticated."
      • addedInput schema / properties / name
        Added value: +{
+  "description": "User's first name if known.",
+  "type": "string"
+}
    • Changedpause_engine2 fields changed
      • changedInput schema / properties / email / description
        Previous value: -"Optional. Stripe-Checkout email if not authenticated."New value: +"Stripe Checkout email if not authenticated."
      • addedInput schema / properties / name
        Added value: +{
+  "description": "User's first name if known.",
+  "type": "string"
+}
    • Addedpreview_message
    • Changedquote3 fields changed
      • addedInput schema / properties / company
        Added value: +{
+  "description": "Business name if known.",
+  "type": "string"
+}
      • addedInput schema / properties / name
        Added value: +{
+  "description": "User's first name if known.",
+  "type": "string"
+}
      • changedInput schema / properties / use_case / description
        Previous value: -"Natural language description of who the user wants to sell to. Example: 'I sell B2B AI tooling to Dutch fintech CFOs hiring their first sales lead. Find me 25 of them with the receipt of why they're in-market right now.'"New value: +"Natural language description of the customers the user wants to reach."
    • Changedresume_engine2 fields changed
      • changedInput schema / properties / email / description
        Previous value: -"Optional. Stripe-Checkout email if not authenticated."New value: +"Stripe Checkout email if not authenticated."
      • addedInput schema / properties / name
        Added value: +{
+  "description": "User's first name if known.",
+  "type": "string"
+}
    • Changedsubscribe1 field changed
      • changedInput schema / properties / quote_id / description
        Previous value: -"A quote_id from quote() with plan=solo, pro, or scale. Example: 'q_pro_abc12345'"New value: +"A quote_id with plan=solo, pro, or scale."
  4. 4 tool updates
    • Addedget_subscription_status
    • Addedmanage_billing
    • Addedpause_engine
    • Addedresume_engine
  5. 1 tool update
    • Addedsubscribe
  6. 12 tool updates
    • First observedbook_meeting
    • First observedenqueue_lead
    • First observedfind_leads
    • First observedget_funnel
    • First observedget_pipeline
    • First observedget_receipts
    • First observedget_replies
    • First observedget_started
    • First observedlist_meetings
    • First observedquote
    • First observedsearch_people
    • First observedset_goal

Related MCP Connectors

Related MCP Servers

  • signal-prospector

    thomasproject-stack
    A
    license
    Not graded
    quality
    C
    maintenance
    Enables B2B prospecting from natural language: detect buying signals, score leads against ICP, enrich decision-makers, and draft personalized outreach messages via Claude.
    2
    MIT

  • mcp-gtm-suite

    mambalabsdev
    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
    87 npm
    1
    MIT

  • SignalPipe

    AbYousef739
    A
    license
    Not graded
    quality
    B
    maintenance
    Agentic sales pipeline that detects buying intent from social feeds, scores leads via an AI swarm, and auto-drafts calibrated replies for prospect nurturing.
    27 npm
    MIT
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources