How do I use CSA Assessment Reports MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@CSA Assessment Reports MCP Server Create a pitch deck for Apptio with 24-month savings projection" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

CSA Assessment Reports MCP Server

by sKumaraguru

Overview Schema Related Servers Score Discussions

Python

Remote

CSA Assessment Reports MCP Server

An MCP (Model Context Protocol) server that gives Bob AI direct access to Cloudability Savings Automation (CSA) assessment reports stored in SharePoint. Sales and CSA teams can create pitch decks, analyze savings projections, and compare coverage—all through natural language.

What It Does

Instead of manually navigating SharePoint, downloading Excel files, and extracting data across 49 sheets, users simply ask Bob:

"Create a pitch deck for Apptio with 24-month savings projection"

Bob uses this MCP server to fetch, process, and return structured data in seconds.

graph LR
    A[User] -->|Natural Language| B[Bob AI]
    B -->|MCP Protocol| C[MCP Server]
    C -->|REST API| D[Backend Service]
    D -->|OAuth 2.0| E[SharePoint]

    style A fill:#4a9eff,color:#fff
    style B fill:#ff8c42,color:#fff
    style C fill:#a855f7,color:#fff
    style D fill:#22c55e,color:#fff
    style E fill:#eab308,color:#000

Related MCP server: SharePoint Online MCP Server

Assessment reports are distributed across 4 SharePoint sites. The primary site holds master reports (consolidated portfolio data), while the other 3 sites share the volume of individual assessment reports across all organizations and payer accounts.

graph TB
    subgraph "SharePoint Online — 4 Sites"
        S1[🗂️ Primary Site: CSAReporting<br/>Master Reports only<br/>Portfolio-wide consolidated data]

        S2[📄 Site 2: CSAReporting 2<br/>Assessment Reports<br/>About one-third of all payer accounts]
        S3[📄 Site 3: CSAReporting 3<br/>Assessment Reports<br/>About one-third of all payer accounts]
        S4[📄 Site 4: CSAReporting 4<br/>Assessment Reports<br/>About one-third of all payer accounts]
    end

    S1 ~~~ S2
    S2 ~~~ S3
    S3 ~~~ S4

    style S1 fill:#eab308,color:#000
    style S2 fill:#4a9eff,color:#fff
    style S3 fill:#4a9eff,color:#fff
    style S4 fill:#4a9eff,color:#fff

Each assessment report is an Excel file with 49 sheets containing compute usage, savings plans, reserved instances, planning models, and projections. Reports are split across 3 sites to manage SharePoint's file volume limits.

Business Value

Time Comparison: Manual vs Bob-Assisted

Step	Manual	With Bob
Find the right report	8-18 min (navigate SharePoint, guess which site)	10 sec (parallel search across all sites)
Download & open file	7 min (50-100MB Excel)	30 sec (server-side download, cached after first access)
Locate data in 49 sheets	10-15 min	15 sec (structured extraction)
Extract & format metrics	15-20 min	15 sec
Create deliverable	10-15 min	60 sec (LLM streaming + file generation)
Total	30-70 min	~2-3 min

graph LR
    subgraph BEFORE[" Manual Process "]
        B[Navigate SharePoint<br/>Download Excel<br/>Find data in 49 sheets<br/>Copy to PowerPoint<br/><br/>30-70 minutes]
    end

    subgraph AFTER[" Bob-Assisted Process "]
        A[Ask Bob in natural language<br/>Auto-fetch, extract, generate<br/><br/>2-3 minutes]
    end

    BEFORE -->|~95x faster| AFTER

    style B fill:#e53e3e,color:#fff
    style A fill:#38a169,color:#fff

Architecture

The project uses a two-service architecture to resolve Pydantic v1/v2 dependency conflicts:

graph TB
    subgraph "AWS Cloud"
        subgraph "API Gateway"
            REST[REST API<br/>Lambda Backend]
            HTTP[HTTP API<br/>Fargate MCP]
        end

        subgraph "Compute"
            LAMBDA[Lambda Function<br/>Backend Service<br/>Pydantic v1 + FastAPI]
            FARGATE[Fargate Task<br/>MCP Server<br/>Pydantic v2 + FastMCP]
        end

        subgraph "Networking"
            VPCLINK[VPC Link]
            CLOUDMAP[Cloud Map<br/>Service Discovery]
        end

        subgraph "Data"
            SP[SharePoint Online<br/>4 Sites]
        end
    end

    REST --> LAMBDA
    HTTP --> VPCLINK
    VPCLINK --> CLOUDMAP
    CLOUDMAP --> FARGATE
    FARGATE -->|calls| REST
    LAMBDA --> SP

    style LAMBDA fill:#22c55e,color:#fff
    style FARGATE fill:#a855f7,color:#fff
    style SP fill:#eab308,color:#000

Component	Runtime	Purpose
Backend Service	Lambda (ARM64)	SharePoint integration, Excel processing, caching
MCP Server	Fargate (ARM64)	MCP protocol handling, tool definitions, LLM communication

MCP Tools

1. `list_assessment_reports`

Find available reports by organization and time period.

{
  "org_id": "113798",
  "payer_account_id": "788915724807",
  "year": 2026,
  "month": 5
}

2. `get_assessment_summary_metrics`

Extract executive summary with key metrics, savings opportunities, and recommendations.

{
  "file_id": "01XXXXXXXXXXXX"
}

3. `get_assessment_sheet`

Retrieve any of the 49 sheets with pagination support (up to 5000 rows/page).

{
  "file_id": "01XXXXXXXXXXXX",
  "sheet_name": "compute_usage.csv",
  "page": 1,
  "page_size": 1000,
  "format": "csv"
}

4. `get_assessment_sheet_names`

List all available sheet names in a report before fetching data.

{
  "file_id": "01XXXXXXXXXXXX"
}

5. `get_master_report_summary`

Get consolidated data across multiple payer accounts.

{
  "file_id": "01XXXXXXXXXXXX",
  "category": "Cat5 EC2>$40M"
}

6. `parse_sharepoint_url`

Parse SharePoint URLs (sharing links or direct) to extract file IDs for other tools.

{
  "url": "https://company.sharepoint.com/sites/site/file.xlsx",
  "return_type": "metadata"
}

Bob Integration

This MCP server integrates with Bob (IBM's AI assistant) to provide natural language access to CSA assessment data. Bob uses a dedicated skill (csa-assessments-analyzer) that connects to this MCP server and automates the full workflow from data retrieval to deliverable generation.

sequenceDiagram
    participant User
    participant Bob
    participant MCP as MCP Server
    participant BE as Backend
    participant SP as SharePoint

    User->>Bob: "Create pitch deck for Apptio"
    Bob->>MCP: list_assessment_reports(org_id, year, month)
    MCP->>BE: POST /api/list_assessment_reports
    BE->>SP: Search across 3 assessment sites (parallel)
    SP-->>BE: Found report in Site 2
    BE-->>MCP: Report metadata with file_id
    MCP-->>Bob: Available reports

    Bob->>MCP: get_assessment_summary_metrics(file_id)
    MCP->>BE: POST /api/get_assessment_summary_metrics
    BE->>SP: Download & cache Excel (4hr TTL)
    BE-->>MCP: Structured metrics JSON
    MCP-->>Bob: Summary data

    Bob-->>User: Formatted pitch deck with projections

What Bob Can Generate

Using the data from this MCP server, Bob produces:

Output	Format	Description
Executive Brief	`.docx`	Professional Word document with savings analysis
Pitch Deck	`.pptx`	PowerPoint presentation with projections
Interactive Dashboard	`.html`	Chart.js-powered dashboard with calculators
Sales Pitch	Inline	Structured narrative with YoY breakdowns

Example Prompts

"Create a pitch deck for Apptio with 24-month savings projection"
"Show flexibility analysis for a 36-month CSA engagement"
"Compare current vs projected coverage for org 113798"
"What sheets are available in this report?"
"Generate an interactive dashboard for IBM"
"What are the non-EC2 savings opportunities?"

Bob Workflow

flowchart LR
    A[User Request] --> B[Find Report]
    B --> C[Extract Metrics]
    C --> D{Output Type?}
    D -->|Analysis| E[Formatted Summary]
    D -->|Pitch Deck| F[.docx + .pptx]
    D -->|Dashboard| G[Interactive .html]

    style A fill:#4a9eff,color:#fff
    style D fill:#ff8c42,color:#fff
    style F fill:#38a169,color:#fff
    style G fill:#38a169,color:#fff

MCP Server Connection

Bob connects to the MCP server via the configured endpoint:

{
  "mcpServers": {
    "csa-assessments-prod": {
      "type": "streamable-http",
      "url": "https://<http-api-id>.execute-api.us-west-2.amazonaws.com/mcp"
    }
  }
}

AWS Deployment

Infrastructure Overview

┌─────────────────────────────────────────────────────┐
│ API Gateway (REST)          API Gateway (HTTP)       │
│ └─ /api/{proxy+}           └─ /mcp/{proxy+}        │
│    → Lambda                    → VPC Link           │
│                                   → Cloud Map       │
│                                      → Fargate      │
├─────────────────────────────────────────────────────┤
│ VPC (Private Subnets)                               │
│ ┌─────────────┐  ┌──────────────┐  ┌───────────┐  │
│ │ Lambda ENI  │  │ Fargate Task │  │ VPC Link  │  │
│ │ (Backend)   │  │ (MCP Server) │  │ ENIs      │  │
│ └─────────────┘  └──────────────┘  └───────────┘  │
├─────────────────────────────────────────────────────┤
│ Supporting Services                                  │
│ • Cloud Map (service discovery with SRV records)    │
│ • ECR (container images)                            │
│ • CloudWatch Logs                                   │
│ • S3 (file cache bucket)                            │
└─────────────────────────────────────────────────────┘

Key Configuration

Resource	Detail
Lambda	Python 3.13, ARM64, 3008MB, 300s timeout
Fargate	256 CPU, 512MB, ARM64, Streamable HTTP transport
VPC Link	Private subnets, Cloud Map service discovery
Cloud Map	A + SRV records for port-aware routing
Cache	S3 bucket with 1-day expiration

Deployment

# Prerequisites: AWS credentials, CodeArtifact access

# 1. Prepare dependencies (Linux ARM64 wheels)
./scripts/prepare-deployment.sh

# 2. Build and push MCP server container
./scripts/build-and-push-ecr.sh

# 3. Deploy with Serverless Framework
serverless deploy --stage dev1 --region us-west-2

# 4. Force ECS task to pull latest image
aws ecs update-service \
  --cluster csa-assessments-mcp-dev1-cluster \
  --service csa-assessments-mcp-dev1-mcp-service \
  --force-new-deployment

Endpoints

After deployment:

Backend API: https://<rest-api-id>.execute-api.us-west-2.amazonaws.com/<stage>/api/health
MCP Server: https://<http-api-id>.execute-api.us-west-2.amazonaws.com/mcp

The backend dynamically routes requests across 4 SharePoint sites:

graph TB
    BE[Backend Service<br/>Dynamic Router]

    BE -->|Master Reports| S1[Site 1: CSAReporting<br/>Portfolio-wide data]
    BE -->|Parallel Search| S2[Site 2: CSAReporting 2<br/>About one-third of assessment reports]
    BE -->|Parallel Search| S3[Site 3: CSAReporting 3<br/>About one-third of assessment reports]
    BE -->|Parallel Search| S4[Site 4: CSAReporting 4<br/>About one-third of assessment reports]

    style BE fill:#22c55e,color:#fff
    style S1 fill:#eab308,color:#000
    style S2 fill:#4a9eff,color:#fff
    style S3 fill:#4a9eff,color:#fff
    style S4 fill:#4a9eff,color:#fff

Users don't need to know which site holds their data
Parallel queries across all 3 assessment sites
Reports distributed across sites to manage SharePoint file volume limits
Automatic caching with 4-hour TTL
Resilient — if one site is unavailable, others continue working

Local Development

Prerequisites

Python 3.13+
uv package manager
Azure AD credentials for SharePoint
Access to CloudWiry CodeArtifact

Setup

# Backend (Pydantic v1)
cd backend && uv sync && cd ..

# MCP Server (Pydantic v2)
cd mcp && uv sync && cd ..

# Configure environment
cp .env.example .env  # Edit with your credentials

# Start both services
./start_all.sh

VSCode

Open the workspace file for automatic interpreter switching between the two projects:

code assessments-mcp-server.code-workspace

Project Structure

assessments-mcp-server/
├── backend/                     # Backend service (Lambda)
│   ├── pyproject.toml          # Pydantic v1 dependencies
│   ├── backend_service.py      # FastAPI application
│   ├── lambda_handler.py       # Lambda entry point (Mangum)
│   ├── settings.py             # Configuration
│   └── src/
│       ├── models/             # Input/output/internal models
│       ├── sharepoint/         # Client, discovery, cache
│       ├── processing/         # Excel, CSV, summary extraction
│       ├── services/           # Business logic
│       └── utils/              # Filename parsing, validators
├── mcp/                        # MCP server (Fargate)
│   ├── pyproject.toml          # Pydantic v2 dependencies
│   ├── mcp_server.py           # FastMCP tool definitions
│   ├── mcp_models.py           # Input validation models
│   └── Dockerfile              # Container image
├── scripts/                    # Deployment scripts
├── serverless.yml              # Infrastructure as Code
└── start_all.sh                # Local dev launcher

Error Handling

All tools return structured error responses:

{
  "error": "Report not found: invalid-id",
  "tool": "get_assessment_summary_metrics",
  "hint": "Use list_assessment_reports to find available reports."
}

License

Internal use only — CloudWiry/Apptio

Version History

0.1.0 (2026-06-16) - Initial implementation
- 6 MCP tools for assessment report operations
- Multi-site SharePoint integration with dynamic routing
- AWS deployment on Lambda + Fargate
- Bob AI integration via Streamable HTTP transport

This server cannot be installed

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quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

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CSA Assessment Reports MCP Server

What It Does

SharePoint Data Layout

Business Value

Time Comparison: Manual vs Bob-Assisted

Architecture

MCP Tools

1. list_assessment_reports

2. get_assessment_summary_metrics

3. get_assessment_sheet

4. get_assessment_sheet_names

5. get_master_report_summary

6. parse_sharepoint_url

Bob Integration

What Bob Can Generate

Example Prompts

Bob Workflow

MCP Server Connection

AWS Deployment

Infrastructure Overview

Key Configuration

Deployment

Endpoints

Multi-Site SharePoint Architecture

Local Development

Prerequisites

Setup

VSCode

Project Structure

Error Handling

License

Version History

Maintenance

Resources

Looking for Admin?

Latest Blog Posts

MCP directory API

1. `list_assessment_reports`

2. `get_assessment_summary_metrics`

3. `get_assessment_sheet`

4. `get_assessment_sheet_names`

5. `get_master_report_summary`

6. `parse_sharepoint_url`