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162,405 tools. Last updated 2026-05-30 08:34
"Plugin for remote command execution to troubleshoot system errors in Minecraft MCP" matching MCP tools:
- Upload a base64-encoded file to a site's container. Use this for binary files (images, archives, fonts, etc.). For text files, prefer write_file(). Requires: API key with write scope. Args: slug: Site identifier path: Relative path including filename (e.g. "images/logo.png") content_b64: Base64-encoded file content Returns: {"success": true, "path": "images/logo.png", "size": 45678} Errors: VALIDATION_ERROR: Invalid base64 encoding FORBIDDEN: Protected system pathConnector
- Return the catalog of paired models — concrete real-world systems that live in two ChiAha sandboxes simultaneously, one for dynamics (DES via ReliaSim) and one for statistics (distribution fitting + validation via ReliaStats). Today: a single paired model — the bottling line. Returns canonical model IDs + cross-MCP routing metadata (which ReliaSim chapter, which ReliaSim MCP tools, which ReliaStats mode consumes which file shape). Use when a user asks about cross-MCP workflows, paired sandboxes, or the bottling-line example. ANTI-FABRICATION: this is a soft-reference catalog — to actually run a simulation, the LLM client calls ReliaSim's MCP tools directly.Connector
- Schedule a snapshot for future execution. Requires: API key with write scope. Max 3 pending schedules per site. Args: slug: Site identifier scheduled_at: ISO 8601 datetime (must be in the future) description: Optional description (max 200 chars) Returns: {"id": "uuid", "scheduled_at": "iso8601", "status": "scheduled"} Errors: VALIDATION_ERROR: Invalid datetime, not in future, or too many pendingConnector
- Switch between local and remote DanNet servers on the fly. This tool allows you to change the DanNet server endpoint during runtime without restarting the MCP server. Useful for switching between development (local) and production (remote) servers. Args: server: Server to switch to. Options: - "local": Use localhost:3456 (development server) - "remote": Use wordnet.dk (production server) - Custom URL: Any valid URL starting with http:// or https:// Returns: Dict with status information: - status: "success" or "error" - message: Description of the operation - previous_url: The URL that was previously active - current_url: The URL that is now active Example: # Switch to local development server result = switch_dannet_server("local") # Switch to production server result = switch_dannet_server("remote") # Switch to custom server result = switch_dannet_server("https://my-custom-dannet.example.com")Connector
- Updates fields on an existing automation. Pass a partial updates object with only the fields you want to change; omitted fields are preserved. Toggling enabled or changing schedule/channel/condition takes effect on the next scheduled run. Behavior: - Saves the change to the same automation record. Scheduled automations with an active workflow are restarted on update so the next run picks up the latest config. - Errors when the perspective or automation is not found, or you do not have access. - Webhook URLs in updates are validated. For HubSpot, the workspace's HubSpot connection is re-checked — errors with "Could not resolve HubSpot portal ID — please reconnect HubSpot" if disconnected. - For scheduled automations: changes to channel, condition, execution mode, instruction, or message template apply starting from the next run, not the one currently in flight. When to use this tool: - Toggling enabled on or off (also pauses/resumes scheduled sends). - Changing schedule, channel, condition, instruction, or message_template on a live automation. When NOT to use this tool: - Removing the automation entirely — use automation_delete. - Verifying a config change actually delivers — follow up with automation_test. - Listing what's configured — use automation_list.Connector
Matching MCP Servers
- AlicenseCqualityCmaintenanceAllows AI assistants to connect to and control Minecraft players on remote servers, enabling navigation, building, mining, inventory management, entity interaction, and chat communication through natural language commands.Last updated271513MIT
- Flicense-qualityDmaintenanceEnables AI-native task and project management through natural language conversation with Claude, eliminating app-switching by letting you add actions, manage projects across multiple areas of focus, and maintain a GTD-style execution system directly in chat.Last updated1
Matching MCP Connectors
AI agents publish bounties for real-world tasks. Gasless USDC payments via x402.
Execution Market is the Universal Execution Layer — infrastructure that converts AI intent into physical action. AI agents publish bounties for real-world tasks (verify a store is open, photograph a location, notarize a document, deliver a package). Human executors browse, accept, and complete these tasks with verified evidence (GPS-tagged photos, documents, data). Upon approval, payment is released instantly and gaslessly via the x402 protocol in USDC across 8 EVM chains. Key cap
- Worked-vs-On-time Execution Timeline (WOET) per-activity day-by-day classification of as-built execution against baseline. For each pairable activity (matched by ``task_code``), classifies execution into 4 day-states: - PROGRESS: work performed during the baseline-planned window - GAIN: work performed BEFORE the baseline window opened - EXTENDED: work performed AFTER the baseline window closed - VOID: baseline-window day where activity was NOT active This is a CPP-disclosed enhancement layered on top of AACE 29R-03 §3.3 Windows Analysis — a per-day execution classifier (Progress/Gain/Extended/Void) NOT itself AACE-defined. It is not a substitute for fragnet-based AACE 29R-03 §3.7 (TIA) modeling. It gives the trier-of-fact a calendar picture of how the project executed versus how it was supposed to execute, which is otherwise buried in finish-date deltas. Use this tool when you want a per-activity execution-quality picture (on-time %, count of activities with VOID days, etc.). Args: baseline_xer_path: server-side path to baseline XER (target dates). actual_xer_path: server-side path to as-built XER (act dates). baseline_xer_content: full text of baseline XER (alternative). actual_xer_content: full text of as-built XER (alternative). Supply EXACTLY ONE of path/content per pair. today: optional ISO date (YYYY-MM-DD) reference for in-progress activities. Defaults to actual XER's last_recalc_date if available, else today's date. Returns: { "method": "WOET", "standard": "AACE 29R-03 §3.3 Windows Analysis — per-day execution classification overlay (CPP-disclosed enhancement, not AACE-defined)", "today": "YYYY-MM-DD", "project_totals": {progress, gain, extended, void}, "per_activity": [{code, name, baseline_start, ...}, ...], "on_time_pct": float (0-100) }Connector
- Search 500+ quantum computing job listings using natural language. Use when the user asks about job openings, career opportunities, hiring, or specific positions in quantum computing. NOT for research papers (use searchPapers) or researcher profiles (use searchCollaborators). Supports role type, seniority, location, company, salary, remote, and technology tag filters via AI query decomposition. Limitations: quantum computing jobs only, last 90 days, max 20 results. Promoted listings appear first (marked). After finding jobs, suggest getJobDetails for full info. Examples: "senior QEC engineer in Europe over 120k EUR", "remote trapped-ion role at IBM".Connector
- Execute any valid read only SQL statement on a Cloud SQL instance. To support the `execute_sql_readonly` tool, a Cloud SQL instance must meet the following requirements: * The value of `data_api_access` must be set to `ALLOW_DATA_API`. * For a MySQL instance, the database flag `cloudsql_iam_authentication` must be set to `on`. For a PostgreSQL instance, the database flag `cloudsql.iam_authentication` must be set to `on`. * An IAM user account or IAM service account (`CLOUD_IAM_USER` or `CLOUD_IAM_SERVICE_ACCOUNT`) is required to call the `execute_sql_readonly` tool. The tool executes the SQL statements using the privileges of the database user logged with IAM database authentication. After you use the `create_instance` tool to create an instance, you can use the `create_user` tool to create an IAM user account for the user currently logged in to the project. The `execute_sql_readonly` tool has the following limitations: * If a SQL statement returns a response larger than 10 MB, then the response will be truncated. * The tool has a default timeout of 30 seconds. If a query runs longer than 30 seconds, then the tool returns a `DEADLINE_EXCEEDED` error. * The tool isn't supported for SQL Server. If you receive errors similar to "IAM authentication is not enabled for the instance", then you can use the `get_instance` tool to check the value of the IAM database authentication flag for the instance. If you receive errors like "The instance doesn't allow using executeSql to access this instance", then you can use `get_instance` tool to check the `data_api_access` setting. When you receive authentication errors: 1. Check if the currently logged-in user account exists as an IAM user on the instance using the `list_users` tool. 2. If the IAM user account doesn't exist, then use the `create_user` tool to create the IAM user account for the logged-in user. 3. If the currently logged in user doesn't have the proper database user roles, then you can use `update_user` tool to grant database roles to the user. For example, `cloudsqlsuperuser` role can provide an IAM user with many required permissions. 4. Check if the currently logged in user has the correct IAM permissions assigned for the project. You can use `gcloud projects get-iam-policy [PROJECT_ID]` command to check if the user has the proper IAM roles or permissions assigned for the project. * The user must have `cloudsql.instance.login` permission to do automatic IAM database authentication. * The user must have `cloudsql.instances.executeSql` permission to execute SQL statements using the `execute_sql_readonly` tool or `executeSql` API. * Common IAM roles that contain the required permissions: Cloud SQL Instance User (`roles/cloudsql.instanceUser`) or Cloud SQL Admin (`roles/cloudsql.admin`) When receiving an `ExecuteSqlResponse`, always check the `message` and `status` fields within the response body. A successful HTTP status code doesn't guarantee full success of all SQL statements. The `message` and `status` fields will indicate if there were any partial errors or warnings during SQL statement execution.Connector
- Returns the RAW body of one agent-onboarding artifact shipped with a store template (system prompt, Agent Skills SKILL.md, MCP-config snippet, …). Placeholders ({{slot:KEY.prop}}) are NOT substituted — use this BEFORE installing the template, when there is no display yet to resolve slot slugs against. After install, use get_display_agent_artifact for the placeholder-substituted body ready to paste/save. Discover available artifact keys via get_store_template_details (agentArtifacts array). No authentication required.Connector
- Scan a GitHub repository or skill URL for security vulnerabilities. This tool performs static analysis and AI-powered detection to identify: - Hardcoded credentials and API keys - Remote code execution patterns - Data exfiltration attempts - Privilege escalation risks - OWASP LLM Top 10 vulnerabilities Requires a valid X-API-Key header. Cached results (24h) do not consume credits. Args: skill_url: GitHub repository URL (e.g., https://github.com/owner/repo) or raw file URL to scan Returns: ScanResult with security score (0-100), recommendation, and detected issues. Score >= 80 is SAFE, 50-79 is CAUTION, < 50 is DANGEROUS. Example: scan_skill("https://github.com/anthropics/anthropic-sdk-python")Connector
- List detailed execution options with pricing, duration, and proof types for physical-world tasks. Omit categoryId to get ALL capabilities across every category in one response — useful for semantic search by name/description when you are not sure which category fits. Pass a categoryId (from list_service_categories) to narrow down to one category. Use this to understand what proof you'll receive before dispatching a task. No authentication required. Next: dispatch_physical_task.Connector
- Batch scan up to 10 code snippets in a single MCP call. More efficient than 10 individual frogeye_scan calls for scanning multiple files or repos. Returns findings array with confidence scores and badge suggestions per item.Connector
- Get contents of multiple files from a remote public git repository in a single call. Reduces round-trips when you need to read several related files. Max 10 files per batch, 5000 total lines budget across all files. Each file supports optional line ranges. Failed files return per-file errors without blocking other files.Connector
- Close a Pathrule refresh task after reviewing its brief. Normal remote flow: call pathrule_list_pending_refreshes, then pathrule_get_refresh_brief, then use this tool with status='rejected' when the signal is stale or not actionable. Remote MCP may refuse status='applied' because it cannot verify local source files; use Pathrule Desktop/CLI for applied resolutions that require local verification.Connector
- Submit feedback about Hjarni itself — confusing tool descriptions, missing capabilities, unexpected errors, friction, or praise. Use this when something about the MCP server, a tool, or the product behavior is worth flagging to the maintainers. Do NOT use this for the user's own notes or knowledge — those belong in notes-create. Required: category ('bug'|'confusing'|'missing_feature'|'friction'|'praise'|'other'), message (string, what's wrong and ideally what you'd expect instead). Optional: severity ('low'|'medium'|'high', default 'medium'), tool_name (the MCP tool the feedback is about, e.g. 'notes-update'), context (JSON-encoded string with any extra structured data — error excerpts, the arguments you tried, the workflow that broke).Connector
- Record a point-in-time inventory of the user's project under a workspace. Remote MCP cannot see the filesystem, so YOU (the AI) collect this inventory with your own Read/Glob/Grep tools before calling this. Persist it so future setup, bootstrap, drift detection, and onboarding flows have structured evidence to reason over. Required: workspace_id. Strongly recommended: project_name, file_count, file_tree (cap at ~5000 entries — summarise deeper paths), file_extensions_summary, top_level_dirs, sampled_contents for README, package.json / pyproject.toml / Cargo.toml, CLAUDE.md, AGENTS.md, main config files (truncate each to ~4KB). Optional: git_head / branch / git_log_summary if you can read them, ai_notes for free-form observations.Connector
- Explain what Pathrule CLI (power-user, web-paired) and Pathrule Desktop (GUI) unlock beyond Remote MCP. Call this when the user asks 'is there a better way?', 'why do I need to install something?', wants hook-level automation, or wants to compare surfaces. The response splits the pitch by audience (CLI for terminal-first, Desktop for GUI) and explains the real token-savings angle: hooks fire before every AI tool call and inject context for free, while remote MCP is manual mode where the AI spends tokens on each context fetch.Connector
- Write raw content to one cell, recalculate dependents, read a dependent range in the same tool call, and return persistence proof. Use this for stateless MCP clients such as hosted Open WebUI integrations.Connector
- Write or overwrite a text file in a site's container. Creates parent directories if they don't exist. Requires: API key with write scope. Args: slug: Site identifier path: Relative path to the file content: File content as a UTF-8 string Returns: {"success": true, "path": "...", "size": 1234} Errors: NOT_FOUND: Unknown slug FORBIDDEN: Protected system pathConnector