An MCP server and composable Go library that connects AI assistants to DataHub metadata catalogs. Search datasets, explore schemas, trace lineage, and access glossary terms and domains.
mcp-datahub.txn2.com | Installation | Library Docs
MCP Data Platform Ecosystem
mcp-datahub is part of a broader suite of open-source MCP servers designed to work together as a composable data platform. Each component can run standalone or be combined to give AI assistants unified access to storage, query engines, and metadata catalogs.
Two Ways to Use
1. Standalone MCP Server
Install and connect to Claude Desktop, Cursor, or any MCP client:
Claude Desktop (Easiest) - Download the .mcpb bundle from releases and double-click to install:
- macOS Apple Silicon:
mcp-datahub_X.X.X_darwin_arm64.mcpb - macOS Intel:
mcp-datahub_X.X.X_darwin_amd64.mcpb - Windows:
mcp-datahub_X.X.X_windows_amd64.mcpb
Other Installation Methods:
# Homebrew (macOS)
brew install txn2/tap/mcp-datahub
# Go install
go install github.com/txn2/mcp-datahub/cmd/mcp-datahub@latest
Manual Claude Desktop Configuration (if not using MCPB):
{
"mcpServers": {
"datahub": {
"command": "/opt/homebrew/bin/mcp-datahub",
"env": {
"DATAHUB_URL": "https://datahub.example.com",
"DATAHUB_TOKEN": "your_token"
}
}
}
}
Multi-Server Configuration
Connect to multiple DataHub instances simultaneously:
# Primary server
export DATAHUB_URL=https://prod.datahub.example.com/api/graphql
export DATAHUB_TOKEN=prod-token
export DATAHUB_CONNECTION_NAME=prod
# Additional servers (JSON)
export DATAHUB_ADDITIONAL_SERVERS='{"staging":{"url":"https://staging.datahub.example.com/api/graphql","token":"staging-token"}}'
Use datahub_list_connections to discover available connections, then pass the connection parameter to any tool.
2. Composable Go Library
Import into your own MCP server for custom authentication, tenant isolation, and audit logging:
import (
"github.com/txn2/mcp-datahub/pkg/client"
"github.com/txn2/mcp-datahub/pkg/tools"
)
// Create client and register tools with your MCP server
datahubClient, _ := client.NewFromEnv()
defer datahubClient.Close()
toolkit := tools.NewToolkit(datahubClient, tools.Config{})
toolkit.RegisterAll(yourMCPServer)
Customizing Tool Descriptions
Override tool descriptions to match your deployment:
toolkit := tools.NewToolkit(datahubClient, tools.Config{},
tools.WithDescriptions(map[tools.ToolName]string{
tools.ToolSearch: "Search our internal data catalog for datasets and dashboards",
}),
)
Customizing Tool Annotations
Override MCP tool annotations (behavior hints for AI clients):
toolkit := tools.NewToolkit(datahubClient, tools.Config{},
tools.WithAnnotations(map[tools.ToolName]*mcp.ToolAnnotations{
tools.ToolSearch: {ReadOnlyHint: true, OpenWorldHint: boolPtr(true)},
}),
)
All 12 tools ship with default annotations: read tools are marked ReadOnlyHint: true; datahub_create is non-destructive and non-idempotent; datahub_update is non-destructive and idempotent; datahub_delete is destructive and idempotent.
Extensions (Logging, Metrics, Error Hints)
Enable optional middleware via the extensions package:
import "github.com/txn2/mcp-datahub/pkg/extensions"
// Load from environment variables (MCP_DATAHUB_EXT_*)
cfg := extensions.FromEnv()
opts := extensions.BuildToolkitOptions(cfg)
toolkit := tools.NewToolkit(datahubClient, toolsCfg, opts...)
// Or load from a YAML/JSON config file
serverCfg, _ := extensions.LoadConfig("config.yaml")
See the library documentation for middleware, selective tool registration, and enterprise patterns.
Combining with mcp-trino
Build a unified data platform MCP server by combining DataHub metadata with Trino query execution:
import (
datahubClient "github.com/txn2/mcp-datahub/pkg/client"
datahubTools "github.com/txn2/mcp-datahub/pkg/tools"
trinoClient "github.com/txn2/mcp-trino/pkg/client"
trinoTools "github.com/txn2/mcp-trino/pkg/tools"
)
// Add DataHub tools (search, lineage, schema, glossary)
dh, _ := datahubClient.NewFromEnv()
datahubTools.NewToolkit(dh, datahubTools.Config{}).RegisterAll(server)
// Add Trino tools (query execution, catalog browsing)
tr, _ := trinoClient.NewFromEnv()
trinoTools.NewToolkit(tr, trinoTools.Config{}).RegisterAll(server)
// AI assistants can now:
// - Search DataHub for tables -> Get schema -> Query via Trino
// - Explore lineage -> Understand data flow -> Run validation queries
See txn2/mcp-trino for the companion library.
Bidirectional Integration with QueryProvider
The library supports bidirectional context injection. While mcp-trino can pull semantic context from DataHub, mcp-datahub can receive query execution context back from a query engine:
import (
datahubTools "github.com/txn2/mcp-datahub/pkg/tools"
"github.com/txn2/mcp-datahub/pkg/integration"
)
// QueryProvider enables query engines to inject context into DataHub tools
type myQueryProvider struct {
trinoClient *trino.Client
}
func (p *myQueryProvider) Name() string { return "trino" }
func (p *myQueryProvider) ResolveTable(ctx context.Context, urn string) (*integration.TableIdentifier, error) {
// Map DataHub URN to Trino table (catalog.schema.table)
return &integration.TableIdentifier{
Catalog: "hive", Schema: "production", Table: "users",
}, nil
}
func (p *myQueryProvider) GetTableAvailability(ctx context.Context, urn string) (*integration.TableAvailability, error) {
// Check if table is queryable
return &integration.TableAvailability{Available: true}, nil
}
func (p *myQueryProvider) GetQueryExamples(ctx context.Context, urn string) ([]integration.QueryExample, error) {
// Return sample queries for this entity
return []integration.QueryExample{
{Name: "sample", SQL: "SELECT * FROM hive.production.users LIMIT 10"},
}, nil
}
// Wire it up
toolkit := datahubTools.NewToolkit(datahubClient, config,
datahubTools.WithQueryProvider(&myQueryProvider{trinoClient: trino}),
)
When a QueryProvider is configured, tool responses are enriched:
- Search results: Include
query_contextwith table availability - Entity details: Include
query_table,query_examples,query_availability - Schema: Include
query_tablefor immediate SQL usage - Lineage: Include
execution_contextmapping URNs to tables
Integration Middleware
Enterprise features like access control and audit logging are enabled through middleware adapters:
import (
datahubTools "github.com/txn2/mcp-datahub/pkg/tools"
"github.com/txn2/mcp-datahub/pkg/integration"
)
// Access control - filter entities by user permissions
type myAccessFilter struct{}
func (f *myAccessFilter) CanAccess(ctx context.Context, urn string) (bool, error) { /* ... */ }
func (f *myAccessFilter) FilterURNs(ctx context.Context, urns []string) ([]string, error) { /* ... */ }
// Audit logging - track all tool invocations
type myAuditLogger struct{}
func (l *myAuditLogger) LogToolCall(ctx context.Context, tool string, params map[string]any, userID string) error { /* ... */ }
// Wire up with multiple integration options
toolkit := datahubTools.NewToolkit(datahubClient, config,
datahubTools.WithAccessFilter(&myAccessFilter{}),
datahubTools.WithAuditLogger(&myAuditLogger{}, func(ctx context.Context) string {
return ctx.Value("user_id").(string)
}),
datahubTools.WithURNResolver(&myURNResolver{}), // Map external IDs to URNs
datahubTools.WithMetadataEnricher(&myEnricher{}), // Add custom metadata
)
See the library documentation for complete integration patterns.
Available Tools
Read Tools (always available)
| Tool | Description |
|---|---|
datahub_search | Search for datasets, dashboards, pipelines by query and entity type |
datahub_get_entity | Get entity metadata by URN (description, owners, tags, domain) |
datahub_get_schema | Get dataset schema with field types and descriptions |
datahub_get_lineage | Get upstream/downstream lineage (supports level=column for column-level) |
datahub_get_queries | Get SQL queries associated with a dataset |
datahub_browse | Browse catalog: list tags, domains, or data products |
datahub_get_glossary_term | Get glossary term definition and properties |
datahub_get_data_product | Get data product details (owners, domain, properties) |
datahub_list_connections | List configured DataHub server connections (multi-server mode) |
Write Tools (require DATAHUB_WRITE_ENABLED=true)
3 CRUD tools using the what discriminator pattern — 37 operations total:
| Tool | Operations | Description |
|---|---|---|
datahub_create | 10 | Create tags, domains, glossary terms, data products, documents, applications, queries, incidents, structured properties, data contracts |
datahub_update | 19 | Update descriptions (including tag/glossaryTerm descriptions), tags, glossary terms, links, owners, domains, structured properties, custom properties, incidents, queries, documents, data contracts |
datahub_delete | 8 | Delete queries, tags, domains, glossary entities, data products, applications, documents, structured properties |
Write tools are disabled by default for safety.
DataHub Version Compatibility
Minimum: DataHub 1.3.x. Full feature set: DataHub 1.4.x.
| DataHub Version | Features |
|---|---|
| 1.3.x+ (minimum) | All read tools, all write operations except documents (tags, domains, glossary, data products, queries, owners, links, descriptions, incidents, applications, structured properties incl. delete, data contracts) |
| 1.4.x+ (full) | + Documents (create/update/delete) |
The client gracefully handles version differences — read queries return empty results (not errors) when a feature is unavailable on older versions.
See the tools reference for detailed documentation.
Configuration
| Variable | Description | Default |
|---|---|---|
DATAHUB_URL | DataHub GraphQL API URL | (required) |
DATAHUB_TOKEN | API token | (required) |
DATAHUB_TIMEOUT | Request timeout (seconds) | 30 |
DATAHUB_DEFAULT_LIMIT | Default search limit | 10 |
DATAHUB_MAX_LIMIT | Maximum limit | 100 |
DATAHUB_CONNECTION_NAME | Display name for primary connection | datahub |
DATAHUB_ADDITIONAL_SERVERS | JSON map of additional servers | (optional) |
DATAHUB_WRITE_ENABLED | Enable write operations (true or 1) | false |
DATAHUB_DEBUG | Enable debug logging (1 or true) | false |
Extensions
| Variable | Description | Default |
|---|---|---|
MCP_DATAHUB_EXT_LOGGING | Enable structured logging of tool calls | false |
MCP_DATAHUB_EXT_METRICS | Enable metrics collection | false |
MCP_DATAHUB_EXT_METADATA | Enable metadata enrichment on results | false |
MCP_DATAHUB_EXT_ERRORS | Enable error hint enrichment | true |
Config File
As an alternative to environment variables, configure via YAML or JSON:
datahub:
url: https://datahub.example.com
token: "${DATAHUB_TOKEN}"
timeout: "30s"
write_enabled: true
toolkit:
default_limit: 20
descriptions:
datahub_search: "Custom search description for your deployment"
extensions:
logging: true
errors: true
Load with extensions.LoadConfig("config.yaml"). Environment variables override file values for sensitive fields. Token values support $VAR / ${VAR} expansion.
See configuration reference for all options.
Development
make build # Build binary
make test # Run tests with race detection
make lint # Run golangci-lint
make security # Run gosec and govulncheck
make coverage # Generate coverage report
make verify # Run tidy, lint, and test
make help # Show all targets
Related Projects
- txn2/mcp-trino (docs) - Composable MCP toolkit for Trino query execution
- DataHub - The open-source metadata platform
Contributing
See CONTRIBUTING.md for guidelines.
License
Open source by Craig Johnston, sponsored by Deasil Works, Inc.