cleanup_workspace

MCP tool from Orionbelt Analytics by ralforion

Delete all workspace files for the current connection and start fresh

How to use it

cleanup_workspace is exposed by the Orionbelt Analytics MCP server. Add the server to your MCP client (Claude Desktop, Cursor, Windsurf and others), and the cleanup_workspace tool becomes available to the model automatically. See the full listing for setup details and every tool this server provides.

Install Orionbelt Analytics

$claude mcp add orionbelt-analytics http://localhost:9000/mcp

FULL ORIONBELT ANALYTICS LISTING

Other tools in Orionbelt Analytics (26)

add_rdf_knowledge

Add custom metadata triples to the RDF store

apply_semantic_names

Apply LLM-suggested semantic names and descriptions to ontology

connect_database

Connect to any supported database using .env credentials

discover_schema

Analyze schema structure with automatic GraphRAG + ontology generation

download_artifact

Download ontology or R2RML mapping as a Turtle file

execute_sql_query

Execute SQL with OBQC validation, security checks, and fan-trap detection

Generate Plotly charts (bar, line, scatter, heatmap) with MCP-UI rendering

generate_ontology

Generate RDF/OWL ontology from schema with SQL mapping annotations

get_semantic_model

Retrieve a stored semantic model by name

get_table_details

Get detailed column, key, and constraint info for a specific table

graphrag_find_join_path

Discover join paths between tables via graph traversal

graphrag_query_context

Get optimized context for SQL generation (85-95% token reduction)

graphrag_search

Semantic search + schema overview (auto-initialized by discoverschema)

List available schemas in the connected database

list_semantic_models

List all stored semantic models for the current connection

load_my_ontology

Load a custom .ttl ontology file from an import folder

measurable_from

Measure-capable tables for an anchor grain (one-to-many closure)

plan_composite_query

Advise a fan-trap-safe Composite Fact Layer (UNION ALL) decomposition

Execute SPARQL queries (SELECT, ASK, CONSTRUCT — auto-detected)

Dimension-capable tables for an anchor grain (many-to-one closure)

Clear cached schema and ontology data for the current session

sample_table_data

Preview table data with row limit and injection protection

save_semantic_model

Save a semantic model (e.g., OBML YAML) to the workspace

store_ontology_in_rdf

Persist ontology in Oxigraph for SPARQL access

suggest_semantic_names

Detect abbreviations and cryptic names for business-friendly renaming