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automatikstudio

ProposalPilot MCP Server

by automatikstudio
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JavaScript
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ProposalPilot MCP Server

An MCP (Model Context Protocol) server that generates professional freelance project proposals using AI.

Features

  • AI-Powered Proposals: Uses Claude to generate compelling, tailored proposals

  • Complete Proposal Structure: Executive summary, scope, timeline, pricing, and terms

  • Customizable Tone: Professional, confident, or friendly writing styles

  • MCP Compatible: Works with any MCP-compatible client (Claude Desktop, etc.)

Installation

cd mcp-servers/proposalpilot-mcp
npm install
npm run build

Configuration

Set your Anthropic API key:

export ANTHROPIC_API_KEY=your-key-here

Claude Desktop

Add to your Claude Desktop config (~/.config/claude-desktop/config.json or ~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "proposalpilot": {
      "command": "node",
      "args": ["/path/to/mcp-servers/proposalpilot-mcp/dist/index.js"],
      "env": {
        "ANTHROPIC_API_KEY": "your-key-here"
      }
    }
  }
}

Tool: generate_proposal

Generates a professional freelance project proposal.

Required Inputs

Parameter

Type

Description

project_description

string

Detailed description of the project requirements (min 10 chars)

client_name

string

Name of the client or company

budget

string

Budget info (e.g., "$100/hr", "$5000 fixed", "$3000-5000")

timeline

string

Desired timeline (e.g., "2 weeks", "by March 15")

Optional Inputs

Parameter

Type

Description

tone

string

Writing tone: "professional", "confident", or "friendly"

services

string

Freelancer's services/skills to highlight

Example

{
  "name": "generate_proposal",
  "arguments": {
    "project_description": "Build a modern e-commerce website with React frontend and Node.js backend. Need product catalog, shopping cart, checkout with Stripe, and admin dashboard.",
    "client_name": "TechStartup Inc",
    "budget": "$8,000 - $12,000",
    "timeline": "6 weeks",
    "tone": "professional",
    "services": "Full-stack web development, React, Node.js, PostgreSQL"
  }
}

Output

Returns a complete proposal with:

  1. Executive Summary - Project understanding and fit

  2. Scope of Work - Detailed deliverables breakdown

  3. Timeline - Milestones and schedule

  4. Pricing - Cost breakdown based on budget

  5. Terms & Conditions - Payment and revision policies

Development

# Run in development mode
npm run dev

# Build
npm run build

# Test
npm test

Testing

The test script validates server startup, tool listing, and (if ANTHROPIC_API_KEY is set) proposal generation:

npm run build
npm test

License

MIT

Available Tools

1 tool
generate_proposalC

Generate a professional freelance project proposal using AI. Creates a complete proposal with executive summary, scope of work, timeline, pricing, and terms.

ParametersJSON Schema
NameRequiredDescriptionDefault
project_descriptionYesDetailed description of the project requirements and goals. Should be at least 10 characters.
client_nameYesName of the client or company the proposal is for.
budgetYesBudget information - can be hourly rate, fixed price, or budget range (e.g., '$100/hr', '$5000 fixed', '$3000-5000').
timelineYesDesired project timeline or deadline (e.g., '2 weeks', 'by March 15', 'ASAP').
toneNoWriting tone for the proposal. Defaults to professional.
servicesNoOptional: Freelancer's services or skills to highlight in the proposal.

TDQS

C2.9/5.0
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 of behavioral disclosure. It mentions AI generation and the output structure but lacks details on permissions, rate limits, error handling, or whether the proposal is saved or editable. For a tool with no annotations, this leaves significant gaps in understanding its operational behavior.

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?

The description is concise and front-loaded, stating the main purpose in the first sentence and listing key components in the second. Both sentences earn their place by clarifying the tool's function and output structure without unnecessary details, though it could be slightly more structured for readability.

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?

Given no annotations, no output schema, and 6 parameters with full schema coverage, the description is moderately complete. It covers the tool's purpose and output components but lacks behavioral context and usage guidelines, making it adequate but with clear gaps for an AI agent to fully understand when and how to invoke it effectively.

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%, so the schema fully documents all parameters. The description adds no additional meaning beyond the schema, such as explaining how parameters interact or providing usage examples. Baseline 3 is appropriate as the schema handles parameter documentation adequately.

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 clearly states the tool's purpose: 'Generate a professional freelance project proposal using AI' with specific components listed (executive summary, scope of work, timeline, pricing, and terms). It uses a specific verb ('Generate') and resource ('freelance project proposal'), though without sibling tools, differentiation isn't applicable. The description avoids tautology by elaborating beyond the name.

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?

The description provides no guidance on when to use this tool versus alternatives, prerequisites, or exclusions. It simply states what the tool does without context for its application, such as when it's appropriate for freelance work versus other proposal types or what scenarios it best fits.

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. Dates show when Glama detected each change.

  1. 1 tool updatev1.0.0
    • First observedgenerate_proposal
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TDQS

B3/5.0
Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined and distinct by default.

Naming Consistency5/5

A single tool inherently has perfect naming consistency, as there are no other tools to compare against. The name 'generate_proposal' follows a clear verb_noun pattern.

Tool Count2/5

A single tool is too few for a server named 'ProposalPilot MCP Server', which suggests a broader scope for managing proposals. This minimal set limits functionality and likely leaves gaps in the proposal lifecycle.

Completeness1/5

The tool set is severely incomplete for the implied domain of proposal management. It only provides generation, with no tools for editing, reviewing, listing, deleting, or other essential CRUD operations, causing significant agent failures.

Resources

Unclaimed servers have limited discoverability.

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