Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
MCP server for DataHub data catalogs. Discover datasets, explore lineage, and access metadata.
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Download the maker’s .mcpb file
The link goes to the maker’s own file; we do not host or repackage it. Open the file and Claude Desktop installs it.
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These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account txn2, which owns the repo
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This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (1.15.1) reached the registry 2 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need MCPB on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, EmbeddedCI BenchPod
Servers in the same category from other makers, sorted by stars.
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MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Drive a BenchPod hardware-in-the-loop bench: power, flash, UART, I2C, CAN, analog and logic.
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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](https://mcp-datahub.txn2.com) | [Installation](https://mcp-datahub.txn2.com/server/installation/) | [Library Docs](https://mcp-datahub.txn2.com/library/)
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.
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:
mcp-datahub_X.X.X_darwin_arm64.mcpbmcp-datahub_X.X.X_darwin_amd64.mcpbmcp-datahub_X.X.X_windows_amd64.mcpbOther Installation Methods:
# Homebrew (macOS)
brew install txn2/tap/mcp-datahub
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" } } } }
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
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.
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)
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", }), )
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.
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.
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.
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:
query_context with table availabilityquery_table, query_examples, query_availabilityquery_table for immediate SQL usageexecution_context mapping URNs to tablesEnterprise 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.
| 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) |
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.
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.
| 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 | `dat
Only the beginning is shown; read the rest in the repo