chore: update catalog data files for v2026.03.05 (#846)

Co-authored-by: rdimitrov <16540482+rdimitrov@users.noreply.github.com>

Author: github-actions[bot]

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

@@ -2,7 +2,7 @@
   "$schema": "https://raw.githubusercontent.com/stacklok/toolhive-core/main/registry/types/data/upstream-registry.schema.json",
   "version": "1.0.0",
   "meta": {
-    "last_updated": "2026-03-05T00:44:50Z"
+    "last_updated": "2026-03-05T14:25:33Z"
   },
   "data": {
     "servers": [
@@ -574,7 +574,7 @@
             "io.github.stacklok": {
               "ghcr.io/stacklok/dockyard/npx/astra-db-mcp:1.2.2": {
                 "metadata": {
-                  "last_updated": "2026-02-26T11:45:46Z",
+                  "last_updated": "2026-03-05T02:57:43Z",
                   "stars": 38
                 },
                 "overview": "## Astra DB MCP Server\n\nThe astra-db-mcp server is a Model Context Protocol (MCP) implementation that enables AI assistants and agents to interact directly with DataStax Astra DB — a cloud-native database service — through a standardized, agent-friendly interface. It allows natural language workflows to query, manage, and manipulate collections and records stored in Astra DB without writing custom database integration code.",
@@ -903,7 +903,7 @@
         "packages": [
           {
             "registryType": "oci",
-            "identifier": "public.ecr.aws/awslabs-mcp/awslabs/aws-api-mcp-server:1.3.16",
+            "identifier": "public.ecr.aws/awslabs-mcp/awslabs/aws-api-mcp-server:1.3.17",
             "transport": {
               "type": "stdio"
             },
@@ -967,9 +967,9 @@
         "_meta": {
           "io.modelcontextprotocol.registry/publisher-provided": {
             "io.github.stacklok": {
-              "public.ecr.aws/awslabs-mcp/awslabs/aws-api-mcp-server:1.3.16": {
+              "public.ecr.aws/awslabs-mcp/awslabs/aws-api-mcp-server:1.3.17": {
                 "metadata": {
-                  "last_updated": "2026-02-26T11:46:01Z",
+                  "last_updated": "2026-03-04T22:50:04Z",
                   "stars": 8259
                 },
                 "overview": "## AWS API MCP Server\n\nThe aws-api MCP server is an MCP (Model Context Protocol) server that enables AI assistants and agents to interact directly and securely with AWS services and APIs through a standardized, protocol-driven interface. It acts as a bridge between your MCP-compatible AI workflows and the breadth of AWS's cloud API surface, allowing natural-language-orchestrated tasks — from exploring resources to managing infrastructure — without manual API coding.",
@@ -1004,12 +1004,22 @@
                       "readOnlyHint": false,
                       "title": "Execute AWS CLI commands"
                     },
-                    "description": "Execute AWS CLI commands with validation and proper error handling. This is the PRIMARY tool to use when you are confident about the exact AWS CLI command needed to fulfill a user's request. Always prefer this tool over 'suggest_aws_commands' when you have a specific command in mind.\n    Key points:\n    - The command MUST start with \"aws\" and follow AWS CLI syntax\n    - Commands are executed in us-east-1 region by default\n    - For cross-region or account-wide operations, explicitly include --region parameter\n    - All commands are validated before execution to prevent errors\n    - Supports pagination control via max_results parameter\n    - Commands can only reference files within the working directory (/tmp/aws-api-mcp/workdir); use forward slashes (/) regardless of the system (e.g. if working directory is 'c:/tmp/workdir', use 'c:/tmp/workdir/subdir/file.txt' or 'subdir/file.txt'); relative paths resolve from the working directory.\n\n    Best practices for command generation:\n    - Always use the most specific service and operation names\n    - Always use the working directory when writing files, unless user explicitly mentioned another directory\n    - Include --region when operating across regions\n    - Only use filters (--filters, --query, --prefix, --pattern, etc) when necessary or user explicitly asked for it\n\n    Command restrictions:\n    - DO NOT use bash/zsh pipes (|) or any shell operators\n    - DO NOT use bash/zsh tools like grep, awk, sed, etc.\n    - DO NOT use shell redirection operators (\u003e, \u003e\u003e, \u003c)\n    - DO NOT use command substitution ($())\n    - DO NOT use shell variables or environment variables\n\n    Common pitfalls to avoid:\n    1. Missing required parameters - always include all required parameters\n    2. Incorrect parameter values - ensure values match expected format\n    3. Missing --region when operating across regions\n\n    Returns:\n        CLI execution results with API response data or error message\n    ",
+                    "description": "Execute AWS CLI commands with validation and proper error handling. This is the PRIMARY tool to use when you are confident about the exact AWS CLI command needed to fulfill a user's request. Always prefer this tool over 'suggest_aws_commands' when you have a specific command in mind.\n    Key points:\n    - The command MUST start with \"aws\" and follow AWS CLI syntax\n    - Commands are executed in us-east-1 region by default\n    - For cross-region or account-wide operations, explicitly include --region parameter\n    - All commands are validated before execution to prevent errors\n    - Supports pagination control via max_results parameter\n    - Commands can only reference files within the working directory (/tmp/aws-api-mcp/workdir); use forward slashes (/) regardless of the system (e.g. if working directory is 'c:/tmp/workdir', use 'c:/tmp/workdir/subdir/file.txt' or 'subdir/file.txt'); relative paths resolve from the working directory.\n    - You can use `--region *` to run a command on all regions enabled in the account.\n    - Do not generate explicit batch calls for iterating over all regions, use `--region *` instead.\n\n    Single Command Mode:\n    - You can run a single AWS CLI command using this tool.\n    - Example:\n        call_aws(cli_command=\"aws s3api list-buckets --region us-east-1\")\n\n    Batch Running:\n    - The tool can also run multiple independent commands at the same time.\n    - Call this tool with multiple CLI commands whenever possible.\n    - Batch calling is especially useful where you need to run a command multiple times with different parameter values\n    - Example:\n        call_aws(\n            cli_command=[\n                \"aws s3api get-bucket-website --bucket bucket1\",\n                \"aws s3api get-bucket-website --bucket bucket2\"\n            ]\n        )\n    - You can call at most 20 CLI commands in batch mode.\n\n    Best practices for command generation:\n    - Always use the most specific service and operation names\n    - Always use the working directory when writing files, unless user explicitly mentioned another directory\n    - Include --region when operating across regions\n    - Only use filters (--filters, --query, --prefix, --pattern, etc) when necessary or user explicitly asked for it\n    - Always use the tool in batch mode whenever it's possible.\n\n    Command restrictions:\n    - DO NOT use bash/zsh pipes (|) or any shell operators\n    - DO NOT use bash/zsh tools like grep, awk, sed, etc.\n    - DO NOT use shell redirection operators (\u003e, \u003e\u003e, \u003c)\n    - DO NOT use command substitution ($())\n    - DO NOT use shell variables or environment variables\n\n    Common pitfalls to avoid:\n    1. Missing required parameters - always include all required parameters\n    2. Incorrect parameter values - ensure values match expected format\n    3. Missing --region when operating across regions\n\n    Returns:\n        CLI execution results with API response data or error message\n    ",
                     "inputSchema": {
                       "properties": {
                         "cli_command": {
-                          "description": "The complete AWS CLI command to execute. MUST start with \"aws\"",
-                          "type": "string"
+                          "anyOf": [
+                            {
+                              "type": "string"
+                            },
+                            {
+                              "items": {
+                                "type": "string"
+                              },
+                              "type": "array"
+                            }
+                          ],
+                          "description": "A single command or a list of complete AWS CLI commands to execute"
                         },
                         "max_results": {
                           "anyOf": [
@@ -1503,8 +1513,8 @@
                   "homepage": "https://awslabs.github.io/mcp/servers/aws-knowledge-mcp-server/"
                 },
                 "metadata": {
-                  "last_updated": "2026-02-26T11:45:45Z",
-                  "stars": 8259
+                  "last_updated": "2026-03-05T02:57:42Z",
+                  "stars": 8338
                 },
                 "overview": "## AWS Knowledge MCP Server\n\nThe aws-knowledge MCP server is a Model Context Protocol server that gives AI assistants structured access to curated AWS knowledge sources, including architectural guidance, best practices, service concepts, and operational recommendations. It's designed to help AI workflows answer conceptual questions about AWS by grounding responses in authoritative knowledge rather than raw documentation alone. The server provides capabilities including architectural guidance access, concept-level reasoning support, contextual discovery, and grounded AI responses to reduce hallucinations by anchoring answers in vetted AWS knowledge sources.",
                 "status": "Active",
@@ -6043,8 +6053,8 @@
                   "homepage": "https://context7.com/"
                 },
                 "metadata": {
-                  "last_updated": "2026-02-26T11:45:45Z",
-                  "stars": 46978
+                  "last_updated": "2026-03-05T02:57:42Z",
+                  "stars": 47708
                 },
                 "overview": "## Context7 Remote MCP Server\n\nThe context7-remote MCP Server is a hosted Model Context Protocol (MCP) server that provides AI assistants with on-demand access to up-to-date library and framework documentation via Context7. Instead of relying on potentially stale training data, AI workflows can retrieve current, version-specific docs and examples for popular programming languages, frameworks, and tools — directly inside an MCP-compatible assistant. The service is designed to help coding and debugging workflows by enabling assistants to access current API documentation and best practices without depending on outdated model training data, thereby reducing the risk of inaccurate suggestions.",
                 "status": "Active",
@@ -11942,8 +11952,8 @@
             "io.github.stacklok": {
               "iwakitakuma/gitlab-mcp:2.0.19": {
                 "metadata": {
-                  "last_updated": "2026-02-26T11:45:47Z",
-                  "stars": 1087
+                  "last_updated": "2026-03-05T14:11:18Z",
+                  "stars": 1136
                 },
                 "overview": "## GitLab MCP Server\n\nThe gitlab MCP server is a Model Context Protocol (MCP) server that enables AI assistants and agents to interact directly with GitLab projects and resources through a structured, AI-friendly interface. It allows AI-driven workflows to work with repositories, issues, merge requests, and project metadata without switching tools or manually navigating the GitLab UI. It is ideal for development, code review, CI/CD visibility, and project management workflows that rely on GitLab as the system of record.",
                 "permissions": {
@@ -15051,7 +15061,7 @@
             "io.github.stacklok": {
               "ghcr.io/stacklok/dockyard/npx/heroku-mcp-server:1.0.7": {
                 "metadata": {
-                  "last_updated": "2026-02-26T11:45:47Z",
+                  "last_updated": "2026-03-05T14:11:18Z",
                   "stars": 74
                 },
                 "overview": "## Heroku MCP Server\n\nThe heroku-mcp-server is a Model Context Protocol (MCP) server that enables AI assistants and agents to interact directly with Heroku applications and platform resources through a structured, AI-friendly interface. It facilitates AI-driven workflows for inspecting apps, managing deployments, reviewing configuration, and assessing runtime state without requiring manual use of the Heroku CLI or dashboard. The tool is particularly suited for application operations, debugging, deployment workflows, and platform management tasks within teams operating workloads on Heroku.",
@@ -16460,7 +16470,7 @@
             "io.github.stacklok": {
               "ghcr.io/stackloklabs/mkp/server:0.2.4": {
                 "metadata": {
-                  "last_updated": "2026-02-26T11:45:46Z",
+                  "last_updated": "2026-03-05T02:57:43Z",
                   "stars": 57
                 },
                 "overview": "## Kubernetes MCP Server\n\nThe k8s MCP server is a Model Context Protocol (MCP) server that enables AI assistants and agents to interact directly with Kubernetes clusters through a structured, AI-friendly interface. It allows AI-driven workflows to inspect cluster state, explore resources, and reason about workloads without switching tools or manually using kubectl or the Kubernetes dashboard. This server is ideal for platform engineering, operations, troubleshooting, and infrastructure-aware AI workflows built on Kubernetes.",
@@ -22554,7 +22564,7 @@
         "packages": [
           {
             "registryType": "oci",
-            "identifier": "docker.io/mongodb/mongodb-mcp-server:1.7.0",
+            "identifier": "docker.io/mongodb/mongodb-mcp-server:1.8.0",
             "transport": {
               "type": "stdio"
             },
@@ -22608,7 +22618,7 @@
         "_meta": {
           "io.modelcontextprotocol.registry/publisher-provided": {
             "io.github.stacklok": {
-              "docker.io/mongodb/mongodb-mcp-server:1.7.0": {
+              "docker.io/mongodb/mongodb-mcp-server:1.8.0": {
                 "metadata": {
                   "last_updated": "2026-03-03T12:34:33Z",
                   "stars": 936
@@ -22695,7 +22705,7 @@
                   "author": "Neon"
                 },
                 "metadata": {
-                  "last_updated": "2026-02-26T11:45:47Z"
+                  "last_updated": "2026-03-05T14:11:18Z"
                 },
                 "overview": "## Neon Remote MCP Server\n\nNeon's official remote MCP server for serverless Postgres with branching and migrations. The server enables project and organization management for Neon Postgres databases, SQL execution with schema and transaction support, database branching for development and testing workflows, plus query tuning and performance optimization features.",
                 "status": "Active",
@@ -22794,7 +22804,7 @@
                   ":8001"
                 ],
                 "metadata": {
-                  "last_updated": "2026-02-26T11:45:46Z",
+                  "last_updated": "2026-03-05T14:11:18Z",
                   "stars": 42
                 },
                 "overview": "## NetBird MCP Server\n\nThe netbird MCP server enables management of a NetBird network through a structured AI-friendly interface. The server offers comprehensive NetBird network management including peer and network configuration, access control via groups and policies, posture checks for security compliance, and port allocation and nameserver management capabilities.",
@@ -41245,8 +41255,8 @@
             "io.github.stacklok": {
               "ghcr.io/korotovsky/slack-mcp-server:v1.2.3": {
                 "metadata": {
-                  "last_updated": "2026-02-26T11:45:46Z",
-                  "stars": 1396
+                  "last_updated": "2026-03-05T14:11:17Z",
+                  "stars": 1423
                 },
                 "overview": "## Slack MCP Server\n\nThe slack-mcp-server is a Model Context Protocol (MCP) server for Slack with channels, DMs, message history, search, and smart pagination. The server connects assistants to Slack workspaces via SSE transport, enabling channel and direct message discovery, message retrieval with threading support, search functionality across messages, and message posting capability.",
                 "permissions": {
@@ -41315,6 +41325,9 @@
                   "homepage": "https://docs.slack.dev/ai/slack-mcp-server",
                   "license": "MIT"
                 },
+                "metadata": {
+                  "last_updated": "2026-03-05T02:57:42Z"
+                },
                 "oauth_config": {
                   "authorize_url": "https://slack.com/oauth/v2_user/authorize",
                   "scopes": [