List all versions of an MCP server - Returns all available versions for a specific MCP server, ordered by publication date (newest first)

Analyze images using Google Lens. Upload an image URL to get visual matches, product identification, text extraction, and exact match detection. Supports refining results with a text query for search types: all, visual_matches, and products.

Get an upload URL to upload a single image to a project. Returns a pre-built upload URL and instructions. The caller must perform the actual upload using curl since the MCP server cannot access local files. This endpoint uploads images only. To add annotations, call annotations_save with the image ID from the upload response. For bulk uploads with annotations, use images_prepare_upload_zip.

Get usage statistics for this MCP server session. Returns tool call counts, success rates, and average latency.

Verify that the FXMacroData API and MCP server are reachable.

Bridge an A2A (Agent-to-Agent Protocol) task to an MCP server. Extracts the intent from the A2A task, maps it to an MCP tool, calls the tool, and wraps the result in A2A response format. Use this to let A2A agents interact with any MCP server. Requires authentication.

Get the current status of the Execution Market MCP server and its integrations. Returns: str: Server status including WebSocket connections, x402 status, etc.

Search for land parcels by parcel ID prefix (autocomplete). Returns matching parcels with their district, area, and GPS coordinates. Useful for finding exact parcel IDs, then searching transactions nearby. Example: search for parcels starting with '146518_8.01'.

Rate and review an MCP server in the ThinkNEO Marketplace. One review per user per package (updates on repeat). Authentication required.

Publish an MCP server to the ThinkNEO Marketplace. Validates the endpoint (calls initialize + tools/list), runs security scan (secrets detection, injection patterns), and stores the entry. Authentication required.

Get installation config for an MCP server from the ThinkNEO Marketplace. Returns ready-to-use JSON config for Claude Desktop, Cursor, Windsurf, or custom clients. Tracks the download. No authentication required.

Get full details for an MCP server package from the ThinkNEO Marketplace. Returns readme, full tools list, version history, reviews, security score, and installation instructions. No authentication required.

Auto-generate an A2A Agent Card from an MCP server's tool list. Each MCP tool is converted into an A2A skill. The resulting agent.json makes the MCP server discoverable by any A2A-compatible agent in Google's agent ecosystem. Defaults to ThinkNEO's own MCP server. Requires authentication.

Returns the full guide for the deBridge MCP server. CALL THIS FIRST.

Submit an MCP server or agent skill to the t00l$hed. Costs toolshed.submit_cost paperclips. Goes through LLM moderation. @lgtm inspects approved submissions.

Search for land parcels by parcel ID prefix (autocomplete). Returns matching parcels with their district, area, and GPS coordinates. Useful for finding exact parcel IDs, then searching transactions nearby. Example: search for parcels starting with '146518_8.01'.

Add a remote MCP server or REST API to your workspace.

Trigger a live trust scan of an HTTP or HTTPS MCP server. Returns trust score, grade, and security findings.

Extracts the background and accent colors from an image. Use this to create a color palette that matches a given image. The input is an image encoded as base64, and the output is a list of brand colors in hex format (e.g., [#041E49, #68748B, #E1E2E8]).

A simple test tool to verify that the MCP server is working correctly

Look up the trust score for any MCP server by URL or npm package name. Returns score, grade, findings summary, and certification status.

Get the current status of the Execution Market MCP server and its integrations. Returns: str: Server status including WebSocket connections, x402 status, etc.

Resize an image to target dimensions. Supports fit modes: 'cover' (crop to fill), 'contain' (fit within, letterbox), 'stretch' (exact size). Useful for preparing images for specific platforms, thumbnails, or social media. FREE. (FREE)

Resize an image to target dimensions. Supports fit modes: 'cover' (crop to fill), 'contain' (fit within, letterbox), 'stretch' (exact size). Useful for preparing images for specific platforms, thumbnails, or social media. FREE. (FREE)

Search Google Images for photos and visual content. Returns image results with thumbnails, source pages, and original image URLs. Useful for finding reference images, illustrations, and visual content.

Get specific MCP server version - Returns detailed information about a specific version of an MCP server. Use the special version `latest` to get the latest version.

Configure automatic top-up when balance drops below a threshold. The configuration lives ONLY in the current MCP session — it is held in memory by the MCP server process and is lost on server restart, MCP client reconnect, or server redeploy. Top-ups are signed locally with TRON_PRIVATE_KEY and sent to your Merx deposit address (memo-routed). For persistent auto-deposit you currently need to call this tool again at the start of each session.

Return the flat MCP billing policy for image/video requests.

Validate whether an MCP server is publishable on real directories (MCP Registry, Smithery, npm). Provide raw artifact contents. Returns evidence-backed findings with source-linked directory rules.

Save an annotation for an existing image.

Search GitHub repositories by topic, language, or description. Returns top repositories with star counts, descriptions, and URLs. Useful for finding libraries, implementations, and examples. Example: 'MCP server Python' or 'agent framework TypeScript'.

Generate an image using the Z-Image model based on the provided prompt and settings. This function is triggered when the user clicks the "Generate" button. It processes the input prompt (optionally enhancing it), configures generation parameters, and produces an image using the Z-Image diffusion transformer pipeline. Returns: tuple: (gallery_images, seed_str, seed_int), - seed_str: String representation of the seed used for generation, - seed_int: Integer representation of the seed used for generation (from mcp-tools/Z-Image-Turbo)

[kiwi] Send feedback to the dev of the Kiwi MCP server.

Get detailed information about a specific MCP server

Creates an edited or extended image given an original image and a prompt.

Get current MCP server connection info: network name, node address, and latest block

Uploads an image. - Upload image of the pet.

Answers who can build an MCP server and explains how Walnai can design, implement, integrate, and deploy custom MCP servers for a business.

Thin MCP adapter that forwards to SettlementWitness and returns the exact receipt JSON.

Run a bounded JSON-RPC conformance probe against another MCP server. The input is a registry ``namespace/name`` string (e.g. ``"com.trycloudflare.candy-josh-writers-balance/yultrace-audit"``); the tool looks up the registry-published ``remotes[].url`` and runs the probe against that URL. Arbitrary URLs are NOT accepted — targets are whitelisted to the official MCP Registry's isLatest+active entries. The probe runs five bounded sub-tests (initialize, tools/list, malformed-body, unknown-method, oversized-params) under hard caps (10 HTTP requests; 30 s wall-clock; 500 KB per response; 50 KB final return size).

Checks that the Strale API is reachable and the MCP server is running. Call this before a series of capability executions to verify connectivity, or when troubleshooting connection issues. Returns server status, version, tool count, capability count, solution count, and a timestamp. No API key required.

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")

Verify that two execution replay contracts represent the same deterministic result. This is the programmatic proof of GeodesicAI's core promise: same input + same rules = same result, every time. Given two replay contracts (e.g. from the original execution and a re-run), this tool compares all component hashes and reports whether the executions are byte-identical. Use this to: - Prove to an auditor that a decision from March 3rd matches a re-run today. - Detect when a rule change has altered execution behavior (input hash matches but canonical trace hash differs → the rules diverged). - Confirm a Blueprint migration didn't change any observable outcomes. Args: api_key: GeodesicAI API key (starts with gai_) contract_a: A replay contract dict (the `replay_contract` field from a prior validate/execute_task response) contract_b: Another replay contract dict to compare against contract_a Returns: replay_match: bool — True if the top-level replay_hash matches (fully identical) contract_version_match: bool matches: dict of field_name → value, for every field that agreed mismatches: dict of field_name → {expected, actual}, for every field that disagreed summary: plain-English one-liner describing the result Interpretation of mismatches: - input_payload_hash: the two runs were fed different data - template_version: the Blueprint was upgraded between runs - solver_registry_hash: the platform itself changed between runs - canonical_trace_hash: same inputs and rules but different execution path (should never happen under determinism; indicates a platform bug) - graph_hash: DAG topology changed between runs

Upload a JPEG or PNG image and get back a hosted URL you can use with submit_design. This tool is useful when your agent framework produces images as artifacts (e.g. base64 strings) and you need to upload them before submitting a design. Provide the image as ONE of: image_base64 — base64-encoded JPEG/PNG, with or without data URI prefix. image_url — publicly accessible image URL (max 5 MB). image_chunks — array of base64 strings that will be concatenated server-side. Use this if your base64 string is too large for a single parameter. Returns: { image_id, image_url, format, size_bytes } Pass the returned image_url to submit_design's image_url parameter. ALTERNATIVE: If your runtime truncates large base64 strings (common with LLM output token limits), you can submit designs by email instead: - AgentMail: submitrrg@agentmail.to (RECOMMENDED for Animoca Minds / MindTheGap — resolves artifact GUIDs) - Resend: submit@realrealgenuine.com Attach the image as JPEG/PNG. Subject: "RRG: Title". Body: wallet: 0x...

Retrieve detailed information for a specific FDIC-insured institution using its FDIC Certificate Number (CERT). Use this when you know the exact CERT number for an institution. To find a CERT number, use fdic_search_institutions first. Args: - cert (number): FDIC Certificate Number (e.g., 3511 for Bank of America) - fields (string, optional): Comma-separated list of fields to return Returns a detailed institution profile suitable for concise summaries, with structured fields available for exact values when needed.

Step 2 of the MCP donation flow. Required inputs: campaign_id, amount, reasoning, and tx_hash. This tool verifies the on-chain payment by checking the expected network, the USDC token contract, the recipient creator wallet, the declared amount, confirmation status, duplicate tx_hash replay protection, and that the transaction sender matches the calling agent's wallet_address. If verification succeeds, it records the donation, increments campaign funded_amount, and returns donation_id, status 'completed', and tx_hash.

Classify image safety (normal / suggestive / explicit). Falcons.ai NSFW detection — 100x cheaper and faster than asking an LLM. Returns classification label and boolean is_nsfw flag. Essential for content moderation pipelines. 2 sats per image, pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='detect_nsfw'.

Export a generated image asset by session and asset ID. Returns the image inline as base64 along with metadata (format, dimensions, size). When running locally (stdio transport), you can optionally provide a destinationPath to save the image to disk. USAGE: After generating an image with generateImage, use the sessionId and assetId to export: exportImageAsset(sessionId="...", assetId="...") To save to disk (local/stdio only): exportImageAsset(sessionId="...", assetId="...", destinationPath="/Users/me/project/images/logo.png")

Resolve a name or partial name to an OpenAlex ID. Returns up to 10 matches with disambiguation hints. ALWAYS use this before filtering by entity — names are ambiguous, IDs are not. Also accepts DOIs directly for quick lookup. Response time ~200ms.

Restore and enhance faces in an image using GFPGAN. Detects all faces via RetinaFace, restores quality (fixes blur, noise, compression artifacts), and pastes them back. Optionally enhances the background using Real-ESRGAN. GPU-accelerated, sub-3s latency. Args: image_base64: Base64-encoded image data containing faces (PNG, JPEG, WebP). upscale: Output upscale factor -- 1 to 4 (default: 2). enhance_background: Whether to enhance background with Real-ESRGAN (default: true). Returns: dict with keys: - image (str): Base64-encoded restored image - format (str): Output image format - width (int): Output width - height (int): Output height - upscale (int): Scale factor applied - processing_time_ms (float): Processing time in milliseconds

Edit an image with natural language instructions. Uses Nano Banana 2 — understands context, handles object addition/removal, style transfer, and inpainting. Returns JSON with image URL. Resolution-tiered pricing: 1K=200 sats, 2K=300 sats, 4K=450 sats. Pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='edit_image' and resolution param.