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EPC Tender Screening

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An MCP-only server for evidence-based EPC tender screening that enables AI agents to run a full screening workflow, extract requirements, match company profiles

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About

An MCP-only server for evidence-based EPC tender screening that enables AI agents to run a full screening workflow, extract requirements, match company profiles, generate compliance matrices, and produce bid/no-bid advisory memos.

README

An MCP-only server for evidence-based EPC tender screening.

This project lets MCP-compatible AI agents:

  • run a full screen_tender workflow,
  • extract tender requirements from uploaded tender text,
  • match requirements against a company profile,
  • generate compliance matrices,
  • produce bid/no-bid advisory memos,
  • search explicit public tender source URLs,
  • search local historical proposal examples for grounding.

The project is designed as a clean public MCP repository. It does not include private company documents, credentials, UI pages, or production tender archives.

Why This Exists

Tender teams spend significant time reading long procurement documents, checking eligibility, finding supporting evidence, and deciding whether to bid. This MCP server gives AI agents a structured tool layer for that workflow while keeping the final decision human-reviewed.

Tools

Tool Purpose
screen_tender Run the full screening workflow end to end
connect_company_profile_text Save uploaded/extracted company profile text as local context
connect_current_tender_text Save uploaded/extracted tender text as current tender
connect_tender_source_urls Allowlist public tender source URLs for discovery
search_public_tenders Search explicit source URLs without crawling the whole internet
get_data_status Show connected data sources and fallback state
extract_tender_requirements Extract tender requirements
match_company_profile Match requirements against company capabilities
generate_compliance_matrix Generate requirement-level compliance rows
generate_bid_no_bid_memo Generate advisory fit/risk scores and recommendation
search_historical_proposals Search local historical proposal examples

Quick Start

npm install
npm run dev

Open:

http://localhost:3000

The root URL returns JSON metadata only. There is no UI.

The Streamable HTTP MCP endpoint is:

http://localhost:3000/api/mcp

The root URL returns JSON metadata only:

curl http://localhost:3000

For local connector testing without auth:

MCP_REQUIRE_AUTH=false npm run dev

On Windows PowerShell:

$env:MCP_REQUIRE_AUTH="false"
npm run dev

Stdio MCP

npm run mcp:stdio

Example Claude Desktop style config:

{
  "mcpServers": {
    "epc-tender-screening": {
      "command": "npm",
      "args": ["run", "mcp:stdio"],
      "cwd": "/absolute/path/to/epc-tender-screening-mcp-showcase"
    }
  }
}

Remote Connector Auth

The repo includes a demo OAuth shim for hosted connector experiments.

Set:

MCP_PUBLIC_BASE_URL=https://your-domain.example
MCP_API_KEY=replace-this-token

Connector values:

MCP URL: https://your-domain.example/api/mcp
Authorization URL: https://your-domain.example/oauth/authorize
Token URL: https://your-domain.example/oauth/token
Client ID: epc-tender-demo-client
Client Secret: epc-tender-demo-secret
Scope: mcp tender:read tender:screen

For production, replace the demo OAuth shim with real OAuth and per-user authorization.

Demo token auth is disabled by default in production. For temporary hosted demos only, set:

MCP_ALLOW_DEMO_AUTH=true
MCP_DEMO_ACCESS_TOKEN=replace-this-demo-token

Do not use the default demo token for a public deployment.

ChatGPT Upload Workflow

Upload company profile and tender files to ChatGPT, then ask:

Extract text from the uploaded company profile and tender files.
Call screen_tender with tender_text and company_profile_text.
Summarize the recommendation, red flags, missing documents, and next human actions.

For one-shot analysis without saving:

Extract text from both uploaded files, then call generate_bid_no_bid_memo with tender_text and company_profile_text.

Public Tender Discovery

This project does not crawl the open internet. It searches explicit sources only.

connect_tender_source_urls
search_public_tenders

Use search_public_tenders for discovery leads only. Upload or connect the actual tender document before screening.

Data Files

Safe example files:

data/company-profile.example.json
data/sample-tender.md
data/historical-proposals.example.json

Private local files are ignored by git:

data/company-profile.local.json
data/current-tender.local.md
data/tender-sources.local.json

Example fallback is disabled by default. To demo with bundled example files:

MCP_ALLOW_EXAMPLE_FALLBACK=true npm run dev

On Windows PowerShell:

$env:MCP_ALLOW_EXAMPLE_FALLBACK="true"
npm run dev

Safety

The bid/no-bid memo is advisory only. Every output should be reviewed by tender, finance, legal, HSE, and management owners before submission.

Do not use this project to automatically submit tenders or make binding commercial decisions.

Development

npm run lint
npm run build
npm run eval

The eval suite runs through the real MCP stdio transport and checks tool exposure, safe failure behavior, screening outputs, and evidence traces.

Docs

CI

GitHub Actions runs:

npm ci
npm run lint
npm run build
npm run eval

License

MIT

from github.com/Shiverion/epc-tender-screening-mcp-showcase

Installing EPC Tender Screening

This server has no published package — it is built from source. Open the repository and follow its README.

▸ github.com/Shiverion/epc-tender-screening-mcp-showcase

FAQ

Is EPC Tender Screening MCP free?

Yes, EPC Tender Screening MCP is free — one-click install via Unyly at no cost.

Does EPC Tender Screening need an API key?

No, EPC Tender Screening runs without API keys or environment variables.

Is EPC Tender Screening hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install EPC Tender Screening in Claude Desktop, Claude Code or Cursor?

Open EPC Tender Screening on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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