budget-evaluation-mcp
MCP server that evaluates engineering budget Excel workbooks against PER budgets, QS estimates, and historical unit rates, producing structured reports with approval recommendations and enabling follow-up Q&A via AI.
README
Engineering Budget Evaluation Agent
Microsoft Agent Framework + GitHub Copilot SDK (gpt-5.6-sol) solution for evaluating engineering
budget workbooks through MCP and Microsoft Teams.
The calculation layer is deterministic. It reads PER Budget, QS Estimation, Vendor Quotation,
MAPPING RULES, Historical Unit Rates, and Summary; maps every priced vendor WBS row; and
normalizes category and total rates to USD/Sqm. GPT-5.6 Sol produces the executive narrative and
answers follow-up questions from the structured results.
Architecture
┌───────────────────────────────┐
│ User / Microsoft Teams │
│ Uploads engineering Excel │
│ workbook for budget review │
└──────────────┬────────────────┘
│
▼
┌───────────────────────────────┐
│ Teams App │
│ - Receives file attachment │
│ - Downloads workbook │
│ - Stores conversation report │
│ - Sends follow-up questions │
└──────────────┬────────────────┘
│
▼
┌───────────────────────────────┐
│ MCP Client │
│ - Calls evaluate_budget_ │
│ workbook tool │
│ - Calls ask_budget_report │
│ - Uses Streamable HTTP │
└──────────────┬────────────────┘
│
▼
┌───────────────────────────────┐
│ Budget Evaluation MCP │
│ - /mcp endpoint │
│ - Validates workbook │
│ - Caches reports │
│ - Returns structured data │
└──────────────┬────────────────┘
│
▼
┌───────────────────────────────┐
│ Deterministic Evaluation │
│ - Reads PER / QS / History │
│ - Maps vendor WBS rows │
│ - Normalizes USD/Sqm │
│ - Calculates variance │
│ - Produces vendor decisions │
└──────────────┬────────────────┘
│
▼
┌───────────────────────────────┐
│ Structured Report Model │
│ - Project metadata │
│ - Vendor totals │
│ - Category comparisons │
│ - Warnings and unmatched │
│ items │
└──────────────┬────────────────┘
│
▼
┌───────────────────────────────┐
│ AI Summary Layer │
│ - GitHub Copilot model │
│ - Generates executive │
│ recommendation │
│ - Answers follow-up Q&A │
└──────────────┬────────────────┘
│
▼
┌───────────────────────────────┐
│ Response Back to User │
│ - Evaluation card │
│ - Summary narrative │
│ - Chat follow-up answers │
└───────────────────────────────┘
Key components
teams_app/— Microsoft Teams bot and UI integrationbudget_agent/server.py— MCP server exposing evaluation and report-query toolsbudget_agent/evaluator.py— Excel validation and deterministic cost comparison logicbudget_agent/agent.py— GitHub Copilot-based narrative and Q&A generationtests/— validation and regression tests for evaluator behavior
Evaluation rules
- Vendor total versus PER Budget:
|variance| <= 10%: approve10% < |variance| <= 20%: conditional approval|variance| > 20%: reject
- Vendor mapped category versus QS Estimate:
|variance| <= 5%: reasonable5% < |variance| <= 15%: review required|variance| > 15%: significant concern
- Vendor mapped category unit rate versus historical USD/Sqm: same ±5% / ±15% thresholds.
Unmapped priced rows and missing benchmarks are reported explicitly.
OUTPUT-style dashboard
The MCP report and Teams Adaptive Card follow the workbook OUTPUT tab:
- Page 1 — Vendor total versus PER Budget
- Page 2 — Vendor mapped category amount versus QS Estimate
- Page 3 — Vendor mapped category USD/Sqm versus Historical Unit Rate
Traffic-light indicators are consistent across the structured JSON and Teams UI:
- 🟢 Green — approve / reasonable
- 🟡 Yellow — conditional approval / review required
- 🔴 Red — reject / significant cost concern
- ⚪ Gray — benchmark missing
Local validation
conda activate agentdev
pip install -e '.[dev,azure]'
pytest -q
ruff check budget_agent tests scripts
python -m budget_agent.server
The MCP endpoint is http://localhost:8000/mcp; health is http://localhost:8000/healthz.
Teams app
cd teams_app
npm install
npm run build
Set the values in teams_app/.env.example, then run npm start. Upload an .xlsx file in Teams;
the bot calls evaluate_budget_workbook over MCP and keeps the returned report ID for follow-up
questions in the same conversation.
Azure deployment
conda activate agentdev
export AZURE_SUBSCRIPTION_ID="$(az account show --query id -o tsv)"
export AZURE_RESOURCE_GROUP="rg-budget-agent"
export AZURE_LOCATION="eastus2"
export ACA_SANDBOX_GROUP="aca-sbx-budget-agent"
export COPILOT_GITHUB_TOKEN="<GitHub token authorized for Copilot requests>"
python scripts/deploy_sandbox.py
export MCP_URL="$(python -c 'import json; print(json.load(open(".azure/sandbox-deployment.json"))["mcp_url"])')"
bash scripts/deploy_teams.sh
The scripts create an Azure Container Apps Sandbox MCP service and a single-tenant Teams bot,
enable the Microsoft Teams channel, and generate .azure/engineering-budget-teams-app.zip for
Teams upload. The .azure/ directory and all deployment-specific identifiers are intentionally
excluded from source control.
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