Illuminate MCP Server

Local-first MCP server for querying Anthology Illuminate data in Snowflake, with interactive MCP App dashboards that render directly in the conversation.

Features

• Local stdio transport (Content-Length framed, with ndjson fallback)
• MCP Apps — interactive UI components (dashboards, schema explorer, insights feed, SQL viewer) rendered inline in the conversation via the MCP Apps extension
• 9 CDM domains with builtin metadata catalog, extensible via Snowflake introspection
• Optional LEARN schema support (Blackboard Open Database Schema, Premium tier)
• Read-only SQL policy with schema/table allowlists
• Metadata-grounded SQL planning without server-side LLM credentials
• Query optimizer — automatic term scoping, smart LIMIT inference, EXPLAIN pre-check for large scans
• Insights engine — automated diagnostic queries with anomaly detection, term-scoped to current academic period
• Adaptive response payloads: summary text, table data, chart hints
• Budget tracking with configurable credit thresholds
• Async query execution for long-running jobs
• Paginated results — dashboard fetches additional rows on scroll via get_result_page
• Planner feedback loop with optional persistence

MCP Apps

This server uses the MCP Apps extension to render interactive UI components directly inside the AI conversation. MCP Apps are supported by Claude Desktop, ChatGPT, VS Code Copilot, and other MCP-compatible hosts.

Available Apps

App	Tool	Description
Results Dashboard	display_query	Interactive table with sorting, filtering, pagination, Chart.js visualization, CSV export, drill-down with follow-up suggestions, cell popovers for JSON/long text
Schema Explorer	open_schema_explorer	Browse domains, entities, columns, and relationships. Modal detail view with Data preview tab. "Analyze in chat" sends queries via sendMessage
Insights Feed	discover_insights	Automated health dashboard — 10 diagnostic checks across CDM domains, term-scoped, severity-ranked cards with "Dig into this" drill-down
SQL Viewer	display_sql	Syntax-highlighted SQL display with copy button, "Run this query" and "Edit and run" actions

How MCP Apps work

1. Tools declare a _meta.ui.resourceUri pointing to a ui:// HTML resource
2. When the host calls a tool with UI binding, it fetches the HTML and renders it in a sandboxed iframe
3. The app receives tool results via ontoolresult and renders the interactive UI
4. The app can call server tools via callServerTool (e.g., paginated data fetch, entity details)
5. The app can send messages to the chat via sendMessage (e.g., drill-down follow-ups)
6. The app can update model context via updateModelContext for background context

Tool selection rules

The server instructs the LLM to use tools in this order:

1. run_query — default for ALL data gathering and analysis. Returns data to the LLM with no UI rendered.
2. display_query — ONLY after analysis is complete and the user should see an interactive dashboard. Re-runs the same SQL (Snowflake caches results, so re-execution is instant and free).
3. display_sql — when the user asks to see or review a generated SQL query.
4. discover_insights — when the user asks for anomalies, red flags, or what they should look at.
5. open_schema_explorer — ONLY when the user explicitly asks to browse the schema.

Supported domains

Domain	Description	Refresh Rate
CDM_LMS	Learning Management System (courses, grades, enrollments, assignments)	Overnight
CDM_SIS	Student Information System (students, terms, programs, registrations)	Daily
CDM_TLM	Teaching & Learning Metadata (telemetry, activity events, Ultra events)	Every 30 min
CDM_ALY	Analytics (course scores, content scores, accessibility)	Every 12 hours
CDM_CLB	Collaborate (virtual classroom sessions, attendance, recordings)	Every 2 hours
CDM_MAP	Cross-system mapping (user and course identity linking)	Every 2 hours
CDM_MEDIA	Video Studio (media content, viewing activity)	Near real-time
CDM_META	Metadata (data sources, instance reference data)	Static
LEARN	Blackboard Learn Open Database Schema (Premium only, opt-in)	Every 4 hours

Quick start

macOS / Linux

Requirements: Python 3.12+ (pyenv recommended)

# 1. Clone and enter the repo
cd illuminate-mcp

# 2. Set Python version
pyenv local 3.12.12

# 3. Install package
python -m pip install -e .

# 4. Install Snowflake connector (required for live queries)
python -m pip install -r requirements-snowflake.txt

# 5. Configure environment
cp .env.example .env
# Edit .env with your Snowflake credentials and desired settings

# 6. Run tests
PYTHONPATH=src python -m unittest discover -s tests -v

# 7. Start the server
illuminate-mcp

Windows

Requirements: Python 3.12+ from python.org or via winget install Python.Python.3.12

# 1. Clone and enter the repo
cd illuminate-mcp

# 2. Install package
python -m pip install -e .

# 3. Install Snowflake connector (required for live queries)
python -m pip install -r requirements-snowflake.txt

# 4. Configure environment
copy .env.example .env
# Edit .env with your Snowflake credentials and desired settings

# 5. Run tests
set PYTHONPATH=src
python -m unittest discover -s tests -v

# 6. Start the server
illuminate-mcp

Claude Code / Claude Desktop configuration

Add the server to your MCP client config. The config file location depends on your platform:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json
• Linux: ~/.config/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "illuminate-mcp": {
      "command": "illuminate-mcp",
      "env": {
        "SNOWFLAKE_ACCOUNT": "your-account",
        "SNOWFLAKE_USER": "your-user",
        "SNOWFLAKE_PASSWORD": "your-password",
        "SNOWFLAKE_ROLE": "your-role",
        "SNOWFLAKE_WAREHOUSE": "your-warehouse",
        "SNOWFLAKE_DATABASE": "your-database",
        "ENABLE_QUERY_EXECUTION": "true",
        "ENABLE_METADATA_INTROSPECTION": "true"
      }
    }
  }
}

Note: Env vars in the client config take precedence over .env. You can put credentials in the client config and keep everything else in .env — the server merges both, with client config winning on conflicts.

Windows note: If illuminate-mcp is not found in PATH after pip install, use the full path to the script: "command": "C:\\Users\\<you>\\AppData\\Local\\Programs\\Python\\Python312\\Scripts\\illuminate-mcp.exe"

The server automatically loads .env from the project directory on startup — no manual env sourcing needed.

Configuration

All configuration is via environment variables in .env. See .env.example for the full template with comments.

Snowflake credentials

Required when ENABLE_QUERY_EXECUTION=true or ENABLE_METADATA_INTROSPECTION=true:

• SNOWFLAKE_ACCOUNT - Account identifier (URL prefix is stripped automatically)
• SNOWFLAKE_USER - Service account username
• SNOWFLAKE_PASSWORD - Service account password
• SNOWFLAKE_ROLE - Query execution role
• SNOWFLAKE_WAREHOUSE - Compute warehouse
• SNOWFLAKE_DATABASE - Target database

Domain and schema allowlists

• ALLOWED_DOMAINS - Comma-separated CDM domains to expose (default: CDM_LMS,CDM_TLM,CDM_ALY)
• ALLOWED_SCHEMAS - Comma-separated schemas for policy enforcement (should match domains)
• ALLOWED_TABLES - Optional table-level allowlist (empty = all tables in allowed schemas)

Domains with no tables in Snowflake are automatically excluded when metadata introspection is enabled.

LEARN schema (opt-in)

The LEARN schema provides access to 191+ raw Blackboard Learn source tables. It requires Illuminate Premium tier.

ENABLE_LEARN_SCHEMA=true

When enabled, LEARN is automatically added to ALLOWED_DOMAINS and ALLOWED_SCHEMAS.

Feature flags

Variable	Default	Description
ENABLE_QUERY_EXECUTION	false	Allow SQL execution against Snowflake
ENABLE_METADATA_INTROSPECTION	false	Load schema from Snowflake instead of builtin catalog
ENABLE_PLANNER_PROBES	false	Preflight SQL candidates for non-empty results
ENABLE_PERSISTENT_FEEDBACK	false	Persist planner feedback to disk
ENABLE_LEARN_SCHEMA	false	Include LEARN schema (Premium only)

Runtime limits

Variable	Default	Description
MAX_ROWS	1000	Maximum rows returned per query
STATEMENT_TIMEOUT_SECONDS	120	Snowflake statement timeout
REQUIRE_QUERY_CONFIRMATION	false	Require approved=true per query (MCP client already provides tool approval)
DEFAULT_SESSION_APPROVAL_MODE	per-query	per-query or approve-all

Budget governance

Variable	Default	Description
MONTHLY_CREDIT_BUDGET	100	Monthly Snowflake credit limit
BUDGET_WARNING_THRESHOLDS	70,85,100	Warning percentages
WAREHOUSE_CREDITS_PER_HOUR	0	Fallback credit estimate rate

Output shaping

Variable	Default	Description
DEFAULT_OUTPUT_MODE	auto	auto, text, table, or viz
MAX_TEXT_SUMMARY_LENGTH	1200	Maximum summary text length

MCP tools

Query tools

Tool	UI	Description
run_query	No	Execute SQL and return results as data (default for all data gathering)
display_query	Results Dashboard	Execute SQL and display interactive dashboard (only for final presentation)
display_sql	SQL Viewer	Display formatted SQL with syntax highlighting and copy button
start_query	No	Start async query execution, returns job ID
get_query_status	No	Poll async job status
get_query_results	No	Retrieve completed async job results
get_result_page	No (app-only)	Fetch paginated rows for dashboard lazy loading

Schema tools

Tool	UI	Description
open_schema_explorer	Schema Explorer	Interactive visual schema browser (only on explicit user request)
list_domains	No	List configured CDM domains
list_entities	No	List entities in a domain
describe_entity	No	Describe entity schema with column definitions

Planning tools

Tool	Description
plan_query	Generate multiple ranked SQL candidates with confidence/complexity
generate_sql	Return recommended SQL (strict + fallback) from plan_query
refine_sql	Refine a failed query into strict and fallback retry candidates
explain_query	Validate SQL against read-only policy

Analytics tools

Tool	UI	Description
discover_insights	Insights Feed	Automated diagnostic scan across configured domains

Governance tools

Tool	Description
get_planner_feedback	Inspect execution feedback statistics
set_session_approval	Switch approval mode (per-query / approve-all)
get_budget_status	Check budget tracking status

MCP resources

URI	Description
illuminate://settings/runtime	Current non-secret runtime configuration
illuminate://metadata/catalog	Full domain and entity metadata snapshot
illuminate://metadata/status	Metadata source and fallback warnings
illuminate://metadata/entities/{domain}	Entity listing for a domain
illuminate://metadata/entity/{domain}/{entity}	Single entity detail
ui://illuminate/results-dashboard	Results Dashboard MCP App HTML
ui://illuminate/schema-explorer	Schema Explorer MCP App HTML
ui://illuminate/insights-feed	Insights Feed MCP App HTML
ui://illuminate/sql-viewer	SQL Viewer MCP App HTML

Query optimizer

The query optimizer runs automatically before every run_query and display_query execution:

1. Term scoping — if the query touches a table with a temporal column and the question doesn't ask for historical/trend data, a current-term date filter is injected automatically (~120 days)
2. Smart LIMIT — non-aggregate queries without a LIMIT get one inferred from the question intent (25 for previews, 200 for lists, 500 for investigations, 5000 for "all")
3. EXPLAIN pre-check — estimates scan size before execution and warns if >10M rows or >500 partitions
4. SELECT * hint — flags queries using SELECT * for potential column reduction
5. Safety wrapper — the optimizer never blocks execution; if it fails, the original SQL runs unchanged

Applied optimizations are returned in optimizations_applied and warnings in optimization_warnings in the query response.

Insights engine

discover_insights runs 10 diagnostic queries across configured CDM domains:

• CDM_LMS: Enrollment trend, zero-activity courses, low normalized scores, attempt completion, low instructor activity
• CDM_TLM: Telemetry event volume
• CDM_ALY: Course accessibility score distribution, stale content scores
• CDM_SIS: Enrollment trend, student status distribution

Queries are scoped to the current academic term (resolved from CDM_LMS.TERM). Findings are severity-ranked (critical/warning/info/ok) with threshold-based anomaly detection. Each insight card includes:

• Severity badge and domain tag
• Metric display with change percentage
• Info icon with explanation of what the check measures
• SQL icon showing the exact query that ran
• "Dig into this" button that sends a follow-up query via sendMessage

Errors from missing schemas are classified as "skipped" (not "failed") for clean UX.

MCP prompts

Prompt	Description
explore_lms_entities	Guided exploration of LMS schema
build_enrollment_trend_query	Guided enrollment trend analysis (optional term parameter)

Query planning workflow

1. Use plan_query to get multiple ranked SQL candidates
2. generate_sql returns the top recommended candidate
3. Execute with run_query (sync) or start_query (async)
4. If no data returned, check no_data_diagnostics.refinement_candidates in the response
5. Use refine_sql to get retry candidates for failed queries
6. Use get_planner_feedback to inspect execution history influencing rankings

MCP compatibility

• Supports MCP Apps extension (SEP-1865, spec 2026-01-26) for inline interactive UI
• Supports prompts/list and prompts/get for clients that resolve prompt payloads explicitly
• Tool execution failures are returned as tools/call results with isError=true
• Supports Content-Length framed stdio (default) and ndjson mode (MCP_STDIO_MODE=ndjson)

Run tests

PYTHONPATH=src python -m unittest discover -s tests -v

Operations

See OPERATOR_RUNBOOK.md for startup checks, troubleshooting, and incident handling.

Architecture

See DESIGN.md for design decisions and system architecture.