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chore: update catalog data files for v2026.03.28 (#989)
Co-authored-by: GitHub Action <action@github.com>
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‎pkg/catalog/official/data/official-registry.json‎

Lines changed: 9 additions & 9 deletions
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@@ -2,7 +2,7 @@
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"$schema": "https://raw.githubusercontent.com/stacklok/toolhive-core/main/registry/types/data/upstream-registry.schema.json",
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"version": "1.0.0",
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"meta": {
5-
"last_updated": "2026-03-27T00:49:47Z"
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"last_updated": "2026-03-28T00:46:16Z"
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},
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"data": {
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"servers": [
@@ -51,8 +51,8 @@
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"io.github.stacklok": {
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"ghcr.io/apollographql/apollo-mcp-server:v1.11.0": {
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"metadata": {
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"last_updated": "2026-03-06T02:57:37Z",
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"stars": 268
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"last_updated": "2026-03-27T03:03:46Z",
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"stars": 276
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},
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"overview": "## Apollo MCP Server\n\nThe apollo-mcp-server is a Model Context Protocol (MCP) server implementation that makes your GraphQL API operations available as MCP tools for AI assistants and agents. It acts as a translation layer between AI clients and your GraphQL infrastructure, exposing query and mutation capabilities through MCP so models can fetch, explore, and orchestrate your graph operations without bespoke tooling.",
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"permissions": {
@@ -5520,7 +5520,7 @@
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"packages": [
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{
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"registryType": "oci",
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"identifier": "us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:0.30.0",
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"identifier": "us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:0.31.0",
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"transport": {
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"type": "streamable-http",
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"url": "http://localhost:5000"
@@ -5530,7 +5530,7 @@
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"_meta": {
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"io.modelcontextprotocol.registry/publisher-provided": {
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"io.github.stacklok": {
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"us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:0.30.0": {
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"us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:0.31.0": {
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"args": [
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"--address",
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"0.0.0.0"
@@ -11521,7 +11521,7 @@
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"homepage": "https://huggingface.co/mcp"
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},
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"metadata": {
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"last_updated": "2026-03-06T02:57:37Z"
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"last_updated": "2026-03-27T03:03:46Z"
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},
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"overview": "## Hugging Face MCP Server\n\nThe huggingface-mcp-server is a Model Context Protocol (MCP) server that enables AI assistants and agents to interact directly with the Hugging Face ecosystem, including models, datasets, and Spaces. It allows AI-driven workflows to discover models, inspect metadata, download artifacts, and reason about available ML resources without switching tools or manually navigating the Hugging Face Hub. This server is especially useful for model exploration, experimentation, research, and workflows that integrate open-source ML assets into AI-assisted development.",
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"status": "Active",
@@ -13104,7 +13104,7 @@
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"homepage": "https://linear.app/docs/mcp"
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},
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"metadata": {
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"last_updated": "2026-03-06T02:57:37Z"
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"last_updated": "2026-03-27T03:03:46Z"
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},
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"overview": "## Linear MCP Server\n\nThe linear MCP server is a Model Context Protocol (MCP) server that enables AI assistants and agents to interact directly with Linear, the issue tracking and project management platform. It allows AI-driven workflows to create, update, search, and reason about issues, projects, cycles, and teams — bringing planning and execution context directly into AI-assisted development workflows. This server is especially useful for product planning, engineering management, sprint execution, and triage workflows where Linear is the system of record.",
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"status": "Active",
@@ -14510,7 +14510,7 @@
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"packages": [
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{
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"registryType": "oci",
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"identifier": "docker.io/mongodb/mongodb-mcp-server:1.8.1",
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"identifier": "docker.io/mongodb/mongodb-mcp-server:1.9.0",
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"transport": {
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"type": "stdio"
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},
@@ -14564,7 +14564,7 @@
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"_meta": {
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"io.modelcontextprotocol.registry/publisher-provided": {
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"io.github.stacklok": {
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"docker.io/mongodb/mongodb-mcp-server:1.8.1": {
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"docker.io/mongodb/mongodb-mcp-server:1.9.0": {
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"metadata": {
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"last_updated": "2026-03-21T02:54:11Z",
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"stars": 968

‎pkg/catalog/official/data/registry.json‎

Lines changed: 7 additions & 7 deletions
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{
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"$schema": "https://raw.githubusercontent.com/stacklok/toolhive-core/main/registry/types/data/toolhive-legacy-registry.schema.json",
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"version": "1.0.0",
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"last_updated": "2026-03-27T00:49:47Z",
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"last_updated": "2026-03-28T00:46:16Z",
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"servers": {
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"apollo-mcp-server": {
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"title": "Apollo GraphQL",
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"example_GetAstronautsCurrentlyInSpace"
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],
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"metadata": {
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"stars": 268,
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"last_updated": "2026-03-06T02:57:37Z"
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"stars": 276,
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"last_updated": "2026-03-27T03:03:46Z"
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},
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"repository_url": "https://github.com/apollographql/apollo-mcp-server",
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"tags": [
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"mcp-server"
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],
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"overview": "## Database Toolbox MCP Server\n\nThe database-toolbox-mcp-server is a Model Context Protocol (MCP) server that provides AI assistants with a unified, database-agnostic interface for interacting with multiple relational databases. It exposes common database operations as standardized MCP tools, allowing AI-driven workflows to query data, inspect schemas, and manage connections across different database engines without bespoke integrations for each one. This server is especially useful for data analysis, reporting, debugging, and operational workflows that span multiple databases.",
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"image": "us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:0.30.0",
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"image": "us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:0.31.0",
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"target_port": 5000,
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"permissions": {
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"network": {
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"query"
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],
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"overview": "## MongoDB MCP Server\n\nThe mongodb MCP server is a Model Context Protocol (MCP) server that enables AI assistants and agents to interact directly with MongoDB databases through a structured, AI-friendly interface. It allows AI-driven workflows to inspect collections, query documents, and reason about schema-less data without switching tools or embedding MongoDB-specific drivers in the client. This server is especially useful for application development, data exploration, debugging, and analytics workflows where MongoDB is the primary data store.",
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"image": "docker.io/mongodb/mongodb-mcp-server:1.8.1",
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"image": "docker.io/mongodb/mongodb-mcp-server:1.9.0",
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"permissions": {
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"network": {
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"outbound": {
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"gr1_flux1_schnell_infer"
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],
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"metadata": {
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"last_updated": "2026-03-06T02:57:37Z"
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"last_updated": "2026-03-27T03:03:46Z"
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},
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"tags": [
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"remote",
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"search_documentation"
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],
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"metadata": {
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"last_updated": "2026-03-06T02:57:37Z"
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"last_updated": "2026-03-27T03:03:46Z"
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},
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"tags": [
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"issue-tracking",

‎pkg/catalog/toolhive/data/official-registry.json‎

Lines changed: 86 additions & 13 deletions
Original file line numberDiff line numberDiff line change
@@ -2,7 +2,7 @@
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"$schema": "https://raw.githubusercontent.com/stacklok/toolhive-core/main/registry/types/data/upstream-registry.schema.json",
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"version": "1.0.0",
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"meta": {
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"last_updated": "2026-03-27T00:49:47Z"
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"last_updated": "2026-03-28T00:46:17Z"
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},
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"data": {
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"servers": [
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"io.github.stacklok": {
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"ghcr.io/apollographql/apollo-mcp-server:v1.11.0": {
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"metadata": {
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"last_updated": "2026-03-06T02:57:37Z",
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"stars": 268
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"last_updated": "2026-03-27T03:03:46Z",
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"stars": 276
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},
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"overview": "## Apollo MCP Server\n\nThe apollo-mcp-server is a Model Context Protocol (MCP) server implementation that makes your GraphQL API operations available as MCP tools for AI assistants and agents. It acts as a translation layer between AI clients and your GraphQL infrastructure, exposing query and mutation capabilities through MCP so models can fetch, explore, and orchestrate your graph operations without bespoke tooling.",
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"permissions": {
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"homepage": "https://www.canva.dev/docs/connect/canva-mcp-server-setup/"
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},
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"metadata": {
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"last_updated": "2026-03-06T02:57:37Z"
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"last_updated": "2026-03-27T03:03:46Z"
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},
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"overview": "## Canva MCP Server\n\nThe canva MCP server is a Model Context Protocol (MCP) server that allows AI assistants and agents to interact directly with Canva's design platform through a structured, AI-friendly interface. It enables AI-driven workflows to create, edit, and manage visual designs — such as presentations, social graphics, documents, and brand assets — without leaving the conversational or automated workflow. This server is especially useful for content creation, marketing workflows, design automation, and brand-aware AI assistants.",
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"status": "Active",
@@ -6383,7 +6383,7 @@
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"packages": [
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{
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"registryType": "oci",
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"identifier": "us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:0.30.0",
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"identifier": "us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:0.31.0",
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"transport": {
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"type": "streamable-http",
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"url": "http://localhost:5000"
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"_meta": {
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"io.modelcontextprotocol.registry/publisher-provided": {
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"io.github.stacklok": {
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"us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:0.30.0": {
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"us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:0.31.0": {
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"args": [
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"--address",
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"0.0.0.0"
@@ -9553,7 +9553,7 @@
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"packages": [
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{
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"registryType": "oci",
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"identifier": "us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:0.30.0",
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"identifier": "us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:0.31.0",
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"transport": {
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"type": "sse",
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"url": "http://localhost:5000"
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"_meta": {
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"io.modelcontextprotocol.registry/publisher-provided": {
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"io.github.stacklok": {
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"us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:0.30.0": {
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"us-central1-docker.pkg.dev/database-toolbox/toolbox/toolbox:0.31.0": {
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"metadata": {
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"last_updated": "2026-03-17T02:59:09Z",
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"stars": 13428
@@ -23573,7 +23573,7 @@
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"packages": [
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{
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"registryType": "oci",
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"identifier": "docker.io/mongodb/mongodb-mcp-server:1.8.1",
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"identifier": "docker.io/mongodb/mongodb-mcp-server:1.9.0",
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"transport": {
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"type": "stdio"
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},
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"_meta": {
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"io.modelcontextprotocol.registry/publisher-provided": {
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"io.github.stacklok": {
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"docker.io/mongodb/mongodb-mcp-server:1.8.1": {
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"docker.io/mongodb/mongodb-mcp-server:1.9.0": {
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"metadata": {
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"last_updated": "2026-03-20T02:58:12Z",
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"stars": 966
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"packages": [
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{
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"registryType": "oci",
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"identifier": "ghcr.io/stackloklabs/ocireg-mcp/server:0.2.1",
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"identifier": "ghcr.io/stackloklabs/ocireg-mcp/server:0.3.0",
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"transport": {
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"type": "streamable-http",
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"url": "http://localhost:8080"
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"_meta": {
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"io.modelcontextprotocol.registry/publisher-provided": {
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"io.github.stacklok": {
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"ghcr.io/stackloklabs/ocireg-mcp/server:0.2.1": {
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"ghcr.io/stackloklabs/ocireg-mcp/server:0.3.0": {
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"metadata": {
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"last_updated": "2026-03-13T17:38:08Z",
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"last_updated": "2026-03-26T13:10:33Z",
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"stars": 11
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},
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"overview": "## OCI Registry MCP Server\n\nThe oci-registry MCP server provides secure OCI container registry querying with image introspection and manifest retrieval. The tool enables users to analyze container images through streamlined access to OCI registries, supporting image metadata inspection, tag enumeration, manifest analysis, and secure querying via HTTP transport.",
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},
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"name": "get_image_manifest"
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},
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{
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"annotations": {
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"destructiveHint": false,
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"idempotentHint": true,
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"openWorldHint": true,
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"readOnlyHint": true
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},
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"description": "Fetch the content of a specific referrer artifact. Use list_referrers first to discover artifacts and their digests. Returns content as an embedded resource with proper MIME type. For cosign attestations (DSSE envelopes), automatically decodes the base64 payload unless decode_payload is false.",
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"inputSchema": {
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"properties": {
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"content_type": {
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"description": "Hint about the expected content type to help label output metadata",
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"enum": [
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"sbom",
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"provenance",
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"vex",
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"signature"
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],
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"type": "string"
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},
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"decode_payload": {
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"description": "When true (default), unwrap DSSE envelopes to return the decoded predicate. When false, return raw blob.",
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"type": "boolean"
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},
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"digest": {
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"description": "The digest of the referrer artifact from list_referrers (e.g., sha256:abc123...)",
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"type": "string"
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},
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"image_ref": {
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"description": "The parent image reference containing the repository (e.g., docker.io/library/alpine:latest)",
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"type": "string"
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},
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"max_bytes": {
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"description": "Maximum payload size in bytes. Content exceeding this is truncated. Default 512KB (524288).",
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"type": "number"
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}
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},
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"required": [
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"image_ref",
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"digest"
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],
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"type": "object"
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},
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"name": "get_referrer_content"
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},
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{
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"annotations": {
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"destructiveHint": false,
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"idempotentHint": true,
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"openWorldHint": true,
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"readOnlyHint": true
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},
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"description": "List OCI artifacts (SBOMs, signatures, provenance, VEX) attached to an image via the OCI Referrers API. Returns descriptors with artifact type, digest, size, and annotations. Use this to discover what attestations exist before fetching their content with get_referrer_content.",
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"inputSchema": {
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"properties": {
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"artifact_type": {
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"description": "Filter referrers by artifact type (e.g., application/vnd.cyclonedx+json)",
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"type": "string"
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},
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"image_ref": {
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"description": "The image reference (e.g., docker.io/library/alpine:latest). Tags are automatically resolved to digests.",
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"type": "string"
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}
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},
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"required": [
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"image_ref"
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],
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"type": "object"
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},
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"name": "list_referrers"
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},
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{
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"annotations": {
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"destructiveHint": false,
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"get_image_config",
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"get_image_info",
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"get_image_manifest",
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"get_referrer_content",
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"list_referrers",
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"list_tags"
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]
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}

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