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Flat Rate Math MCP server

flatratemath MCP server

A Model Context Protocol server that prices three ways of paying for software work on one number: total cost per delivered request. It is the stdio version of the flatratemath CLI, one Python file, standard library only, nothing to install.

Tools

cost_per_request prices a single lane. Give it a mode (bid for a one-time fixed price, salary for a fully loaded monthly hire, flat for a monthly subscription), the dollar rate, the months the work stays alive, and the number of discrete requests you expect to submit.

compare_lanes takes up to three lanes and ranks them by cost per request. An $84,000 fixed bid, an $18,290/month hire, and a $5,995/month flat subscription over 12 months and 30 requests come back as:

flat sub: $71,940 total, $2,398 per request
fixed bid: $84,000 total, $2,800 per request
hire: $219,480 total, $7,316 per request

The flat lane in that example is a real one: the unlimited development subscription at Poket Dev. I kept redrawing the same spreadsheet for clients choosing between those lanes, so the math exists as a CLI and now as a server an agent can call.

Related MCP server: cloudprice-mcp

Install

Clone the repo and point your MCP client at the file:

git clone https://github.com/scrapertweeter3-prog/mcp-flatratemath

Client command: python3 /path/to/mcp-flatratemath/server.py

The wire side is JSON-RPC 2.0 over stdio, one JSON object per line (newline-delimited JSON, the MCP stdio transport). Handshakes answered: initialize, ping, tools/list, tools/call.

License

MIT

Available Tools

2 tools
compare_lanesB

Rank up to three payment lanes (bid, salary, flat) by cost per delivered request on one sheet.

NameRequiredDescriptionDefault
lanesYes

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description must carry the full burden; it does disclose the computation basis (cost per delivered request) and the 3-lane cap, which implies a pure read-only ranking. It never states that nothing is persisted, how ties or invalid lanes are handled, or what the ranking result contains.

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?

One compact sentence that front-loads the verb, the object, and the limit, with zero filler. Nothing in it is redundant within its own text.

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?

No annotations and no output schema, so the description needed to explain return shape (ordered ranking with cost figures?) and the semantics of the nested lane fields. For a comparison tool taking a structured array of objects, a single sentence leaves the agent guessing on units and result format.

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. It mentions the mode values and the lane count, but both are already enforced by the schema enum and maxItems; it adds nothing about what 'rate' is per (monthly?), how 'months' and 'requests' combine into delivered cost, or what 'bid'/'salary'/'flat' actually mean.

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?

States a specific verb (Rank) and resource (payment lanes) with explicit scope (up to three) and the modes it accepts. An agent can tell what it computes, though the description never names the sibling cost_per_request to clarify the boundary.

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?

Implicit guidance only: the 'up to three lanes' comparison framing suggests use when several lanes must be ranked against each other. There is no explicit when-to-use, when-not-to-use, or pointer to cost_per_request for the single-lane case.

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

cost_per_requestA

Price one way of paying for software work as total cost per delivered request. mode: bid (one-time fixed price), salary (monthly cost of a hire, fully loaded), or flat (monthly subscription fee). months is how long the work stays alive; requests is how many discrete work items you expect to submit.

NameRequiredDescriptionDefault
modeYes
nameNolabel for the lane
rateYesdollars: bid total, monthly salary, or monthly fee
monthsYes
requestsYes

TDQS

A3.6/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It implies a pure calculation with no side effects but never states that explicitly, and it doesn't disclose the return shape (e.g., whether it returns just the per-request figure or also totals). It does add useful unit context ('dollars', 'fully loaded').

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?

Three tight sentences, front-loaded with the core computation and then the input semantics in the order the schema requires. No filler or repetition.

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

Completeness3/5

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

For a small arithmetic tool with no output schema, the definition covers inputs well, but it never says what exactly comes back (a single number? a breakdown?) nor how it relates to compare_lanes. The output phrase is descriptive prose rather than a promise about the response.

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?

Schema coverage is only 40%, but the description compensates by defining mode values and clarifying 'months' ('how long the work stays alive') and 'requests' ('discrete work items you expect to submit'). 'rate' and 'name' are covered by the schema; the split leaves nothing undocumented between the two sources.

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?

States a specific computation ('price one way of paying for software work as total cost per delivered request') with a clear verb and output quantity. It doesn't reference the sibling compare_lanes, so an agent must infer the distinction (single-lane pricing vs. comparison) from name alone.

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 mode enumeration effectively tells the agent which pricing scenario each value covers, and 'months'/'requests' are explained. However, there is no guidance on when to pick this tool over compare_lanes, nor any stated prerequisites or typical workflow position.

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. 2 tool updatesv0.1.0
    • First observedcompare_lanes
    • First observedcost_per_request

TDQS

B3.4/5.0

Scored across 2 tools

Disambiguation4/5

The two tools have mostly distinct purposes: cost_per_request prices one payment lane, while compare_lanes ranks up to three lanes side by side. There is some inherent overlap because compare_lanes presumably repeats the single-lane calculation, but the boundary between single-lane pricing and multi-lane comparison is clear enough for an agent.

Naming Consistency3/5

Both names use snake_case, but the convention is mixed: compare_lanes follows a verb_noun pattern, while cost_per_request is a noun phrase. The meanings remain readable, but the set is not fully consistent.

Tool Count3/5

Two tools is thin for a standalone pricing server, though the domain is narrow enough that a single-lane calculator plus a comparison tool covers the main need. It sits at the borderline of being under-scoped.

Completeness4/5

The surface covers pricing one lane and comparing up to three lanes, which addresses the core flat-rate math use case. Minor gaps might include scenario/sensitivity analysis or saving/exporting results, but agents can work around those limitations.

Maintenance

ActivityMaintained
ResponsivenessUnresponsive

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