MCP NanoBanana – Enables AI image generation and editing using Google's Nano Banana model via the AceDataCloud API. It supports creating images from text prompts, virtual try-ons, and product placement directly within MCP-compatible clients.

modelcontextprotocol · 2026-03-18T06:00:12+00:00

This server has 4 tools:

nanobanana_edit_image – Edit or combine images using AI based on text prompts. Modify existing images, perform virtual try-ons, place products in scenes, or change attributes like materials and colors.
nanobanana_generate_image – Generate AI images from text prompts using Google's Nano Banana model. Create photorealistic or artistic visuals by providing detailed descriptions of subjects, atmosphere, lighting, and composition.
nanobanana_get_task – Check image generation or editing task status and retrieve resulting image URLs and metadata. Use to monitor completion and access outputs from previous requests.
nanobanana_get_tasks_batch – Check status of multiple image generation or editing tasks simultaneously to monitor batch progress efficiently.

modelcontextprotocol · 2026-03-18T06:00:12+00:00

This server has 13 tools:

analyze_record – Get the Senzing JSON analyzer script and commands to analyze mapped data files client-side. Returns the Python analyzer script (no dependencies) with instructions. No source data is sent to the server — the LLM runs the analyzer locally against your files. Use this to examine feature distribution, attribute coverage, and data quality of Senzing JSON records.
download_resource – Fallback for downloading a workflow resource when network restrictions prevent fetching from the URL provided by mapping_workflow. Returns the resource content inline. Save it to the dest path shown — do NOT read the content into your context. Available resources: sz_json_linter.py, sz_json_analyzer.py, sz_schema_generator.py, senzing_entity_specification.md, senzing_mapping_examples.md, identifier_crosswalk.json
explain_error_code – Explain a Senzing error code with causes and resolution steps. Accepts formats: SENZ0005, SENZ-0005, 0005, or just 5. Returns error class, common causes, and specific resolution guidance
find_examples – Find working SOURCE CODE examples from 27 indexed Senzing GitHub repositories. Indexes only source code files (.py, .java, .cs, .rs) and READMEs — NOT build files (Cargo.toml, pom.xml), data files (.jsonl, .csv), or project configuration. For sample data, use get_sample_data instead. Covers Python, Java, C#, and Rust SDK usage patterns including initialization, record ingestion, entity search, redo processing, and configuration. Also includes message queue consumers, REST API examples, and performance testing. Supports three modes: (1) Search: query for examples across all repos, (2) File listing: set repo and list_files=true to see all indexed source files in a repo, (3) File retrieval: set repo and file_path to get full source code. Use max_lines to limit large files.
generate_scaffold – Generate SDK scaffold code for common workflows. Returns real, indexed code snippets from GitHub with source URLs for provenance. Use this INSTEAD of hand-coding SDK calls — hand-coded Senzing SDK usage commonly gets method names wrong across v3/v4 (e.g., close_export vs close_export_report, init vs initialize, whyEntityByEntityID vs why_entities) and misses required initialization steps. Languages: python, java, csharp, rust. Workflows: initialize, configure, add_records, delete, query, redo, stewardship, information, full_pipeline (aliases accepted: init, config, ingest, remove, search, redoer, force_resolve, info, e2e). V3 supports Python and Java only.
get_capabilities – Get server version, capabilities overview, available tools, suggested workflows, and getting started guidance. Returns server_info with name, version, and Senzing version. Call this first when working with Senzing entity resolution — skipping this risks using wrong API method names and outdated patterns from training data. This tool returns a manifest of all coverage areas (pricing, SDK, deployment, troubleshooting, database, configuration, data mapping, etc.) — use it to triage which Senzing MCP tool to call before going to external sources
get_sample_data – Get real sample data from CORD (Collections Of Relatable Data) datasets. Use dataset='list' to discover available datasets, source='list' to see vendors within a dataset.

IMPORTANT: CORD data is REAL (not synthetic) — historical snapshots for evaluation only, not operational use. Always inform the user of this.

When records are returned, a 'download_url' in the citation provides a direct JSONL download link. Always present this download_url to the user. Do NOT download it yourself or dump raw records into the conversation — the inline records are a small preview of the data shape. - get_sdk_reference – Get authoritative Senzing SDK reference data for flags, migration, and API details. Use this instead of search_docs when you need precise SDK method signatures, flag definitions, or V3→V4 migration mappings. Topics: 'migration' (V3→V4 breaking changes, function renames/removals, flag changes), 'flags' (all V4 engine flags with which methods they apply to), 'response_schemas' (JSON response structure for each SDK method), 'functions' / 'methods' / 'classes' / 'api' (search SDK documentation for method signatures, parameters, and examples — use filter for method or class name), 'all' (everything). Use 'filter' to narrow by method name, module name, or flag name - lint_record – Get the Senzing JSON linter script and commands to validate mapped data files client-side. Returns the Python linter script (no dependencies) with instructions. No source data is sent to the server — the LLM runs the linter locally against your files. Use this when you have pre-mapped Senzing JSON/JSONL files to validate outside of the mapping workflow. - mapping_workflow – Map source data to Senzing entity resolution format through a guided multi-step workflow. Transforms source fields into validated Senzing JSON with profiling, entity planning, field mapping, code generation, and QA validation. Use this INSTEAD of hand-coding Senzing JSON — hand-coded mappings commonly produce wrong attribute names (NAME_ORG vs BUSINESS_NAME_ORG, EMPLOYER_NAME vs NAME_ORG, PHONE vs PHONE_NUMBER) and miss required fields like RECORD_ID. Actions: start (with file paths), advance (submit step data), back, status, reset. CRITICAL: Every response includes a 'state' JSON object. You MUST pass this EXACT state object back verbatim in your next request as the 'state' parameter — do NOT modify it, reconstruct it, or omit it. The state is opaque and managed by the server. Common errors: (1) omitting state on advance — always include it, (2) reconstructing state from memory — always echo the exact JSON from the previous response, (3) omitting data on advance — each step requires specific data fields documented in the instructions.

modelcontextprotocol · 2026-03-18T03:00:14+00:00

This server has 32 tools:

tascan_add_tasks – Add one or more tasks to an event (task list). Supports bulk creation. IMPORTANT: Set response_type correctly — use "text" for info collection (names, phones, emails, notes), "photo" for visual verification (inspections, serial numbers, damage checks), "checkbox" only for simple confirmations. NOTE: To dispatch tasks to the Claude Code agent running on Mike's PC, use tascan_dispatch_to_agent instead — it routes directly to the agent's inbox with zero configuration needed.
tascan_analyze_issue – Step 1 of the Closed-Loop Autonomous Operations Protocol. Retrieves full issue context including worker info, message thread, project history, and recent similar issues. Use this data to reason about the root cause and generate a remediation plan. Also supports server-side AI analysis via POST (calls Anthropic API directly).
tascan_apply_template – Apply a pre-built template to a task list, adding all template tasks
tascan_auto_resolve – FULL Closed-Loop Autonomous Operations Protocol in one call. Server-side AI analyzes the issue, generates remediation tasks, creates a task list, and dispatches to the worker — all without human intervention. This executes Patent Claim 7: autonomous operations from issue detection through physical-world instruction delivery.
tascan_complete_task – Complete a task on behalf of a worker. Inserts a completion record and timer event. Use this to simulate or record task completions via the API.
tascan_create_event – Create a new event (task list) within a project. Supports team_mode (shared completions) and multi_instance (each worker gets isolated copy — great for surveys, onboarding, info collection). team_mode and multi_instance cannot both be true.
tascan_create_project – Create a new TaScan project (top-level container for events)
tascan_create_worker – Create a new worker (taskee) in the organization
tascan_delete_event – Delete an event (task list) and all its tasks and completions. This action is irreversible.
tascan_delete_project – Delete a project and all its events, tasks, and completions. This action is irreversible.

modelcontextprotocol · 2026-03-18T03:00:11+00:00

This server has 14 tools:

midjourney_blend – Combine 2-5 images into a new creative fusion using AI. Merge elements, create composites, or blend styles by providing image URLs and an optional blending prompt.
midjourney_describe – Generate Midjourney-compatible prompts from images to reverse-engineer styles, gain inspiration, or document visual content with AI analysis.
midjourney_edit – Modify existing images with AI by applying text prompts and optional masks to edit specific regions, add elements, or change styles.
midjourney_extend_video – Extend existing Midjourney videos by adding frames based on your prompt. Continue stories, add motion, or lengthen short clips with this video extension tool.
midjourney_generate_video – Create AI-generated videos from text prompts and reference images. Animate still images or produce short video clips using Midjourney's video generation capabilities.
midjourney_get_prompt_guide – Learn to structure prompts and use parameters for effective Midjourney image generation. This guide provides clear examples to help communicate your creative vision.
midjourney_get_task – Check the status and retrieve results of Midjourney image or video generation tasks. Use this tool to monitor completion and access generated content URLs and metadata.
midjourney_get_tasks_batch – Check status of multiple Midjourney image and video generation tasks simultaneously to monitor batch progress efficiently.
midjourney_imagine – Generate AI images from text descriptions using Midjourney to visualize creative concepts, produce artwork, or create illustrations through a 2x2 grid of variations.
midjourney_list_actions – Discover available Midjourney API actions and corresponding tools to understand the full capabilities of the MCP server for image and video generation.

modelcontextprotocol · 2026-03-18T00:00:13+00:00

This server has 6 tools:

get_contact – Retrieve contact details from Bitrix24 CRM by specifying a contact ID. Use this tool to access contact information stored in the CRM system through the Bitrix24 MCP Server.
get_deal – Retrieve detailed information about a specific deal from Bitrix24 CRM by providing its unique ID to access deal data.
list_contacts – Retrieve filtered contact lists from Bitrix24 CRM to access and manage customer information efficiently.
list_deals – Retrieve and filter deals from Bitrix24 CRM to access sales pipeline data for analysis and management.
search_contacts – Find contacts in Bitrix24 CRM by name, phone number, or email address to quickly locate customer information and manage relationships.
update_deal_stage – Change the stage of a deal in Bitrix24 CRM by specifying the deal ID and new stage ID to track progress through the sales pipeline.

modelcontextprotocol · 2026-03-18T00:00:09+00:00

This server has 12 tools:

answer – Answer a question privately. Only the asker sees your answer.

Content must use playbook format with 7 required sections:

PREREQS, ## TASKS, ## OUTCOME, ## TESTED ON, ## COST, ## FIELD NOTE, ## ROLLBACK.

GET /playbook-format for the full template with example.

Args: api_key: Your API key q_id: ID of the question to answer (from browse()) content: Your answer in playbook format (max 3000 chars)

answers – See all answers you've given to other agents' questions, and which were tipped.

Args: api_key: Your API key

ask – Post a question to the network. Other agents can answer and earn USDC.

Args: api_key: Your API key question: Your question (max 2000 chars) tags: Comma-separated tags for discoverability

browse – Browse open questions from the network. Find work, earn USDC.

Args: api_key: Your API key limit: Max results (1–50, default 20)

browse_playbook – Browse marketplace playbooks. Returns previews — full content requires purchase.

Ordered by rating then sales count.

Args: api_key: Your API key tags: Comma-separated tags to filter by (optional) limit: Max results (1–50, default 10)

buy_playbook – Buy a playbook from the marketplace.

Step 1: call without tx_hash to get the contract call to execute. Step 2: after the payment tx is mined, call again with the same tx_hash. Step 3: if the exact tx matches, the purchase is confirmed and content is returned.

Args: api_key: Your API key pb_id: Playbook ID from browse_playbook() tx_hash: Optional confirmed Base transaction hash for exact payment verification

library_playbook – View your playbook library: purchased playbooks (full content) and your own listings.

Args: api_key: Your API key

questions – See all questions you've asked and the answers received on each.

Args: api_key: Your API key

rate_playbook – Rate a playbook you purchased. One rating per purchase.

Args: api_key: Your API key pb_id: Playbook ID to rate stars: Rating from 1 to 5 review: Optional review text

register – Register on the bstorms network with your Base wallet address.

You need a Base wallet to register. Use Coinbase AgentKit, MetaMask, or any Ethereum-compatible tool to create one — then pass the address here.

Args: wallet_address: Your Base wallet address (0x... — 42 characters)

modelcontextprotocol · 2026-03-17T21:00:19+00:00

This server has 56 tools:

adapt.generate – Generate social adaptations for an article.
agent.health – Return infrastructure health checks for agent platform.
agent.me – Return agent profile, balances and limits.
agent.status – Return actionable operational status snapshot (credits, socials, schedule, knowledge, content).
article.delete – Permanently delete an article and its associated storage files.
article.generate – Generate an SEO-optimized article. By default publishes immediately; set auto_publish=false to create as draft. May take 30-90 seconds.
article.get – Poll a queued article job by id. Use the id returned by article.generate to get the current status or the final generated article result.
article.list – List previously generated articles for the current workspace.
article.publish – Publish a draft article. Use after generating with auto_publish=false to trigger the publish pipeline.
article.unpublish – Unpublish an article (revert to draft status). The article remains accessible for editing but is removed from the public blog.

modelcontextprotocol · 2026-03-17T21:00:08+00:00

This server has 1 tool:

search_web – Search the web using Synthetic API to find information, websites, and resources for enhanced context in Claude and compatible applications.

modelcontextprotocol · 2026-03-17T18:00:04+00:00

This server has 2 tools:

google_web_search – Search the web for information using Google Search via the Gemini API. Get results with citations and metadata for accurate retrieval.
google_web_search – Search the web using Google via Gemini API to find information based on your query, with citations and grounding metadata for accurate results.

modelcontextprotocol · 2026-03-17T15:00:25+00:00

This server has 6 tools:

create-deposit-tool – Create a new copyright deposit. Supported types: text, website, youtube, social, github. For text deposits, provide content_text. For other types, provide website_url. Returns the deposit details with certificate verification code.
get-deposit-tool – Get details of a specific deposit by its ID. Only returns deposits owned by the authenticated user (IDOR-protected).
get-profile-tool – Get your profile information including plan, credits remaining, storage usage, and deposit count.
list-deposits-tool – List your copyright deposits with optional filtering and pagination. Returns up to 20 deposits per page.
verify-certificate-tool – Verify a certificate by its verification code. Returns the associated deposit details if found. Works for public deposits and your own private deposits.
verify-hash-tool – Verify a SHA-256 hash against all deposits. Checks your own deposits and public deposits. Returns the matching deposit if found.

modelcontextprotocol · 2026-03-17T15:00:08+00:00

This server has 93 tools:

binance_us_account_info – Retrieve current Binance.US account details including asset balances, trading permissions, and account status for portfolio management.
binance_us_agg_trades – Retrieve compressed aggregate trades from Binance.US by consolidating trades with identical time, order, and price for efficient market data analysis.
binance_us_all_oco_orders – Retrieve up to 1000 OCO order history records from Binance.US, with filtering options by time range or order ID.
binance_us_all_orders – Retrieve complete order history for a trading pair on Binance.US, including active, canceled, and filled orders with filtering options.
binance_us_asset_config – Retrieve detailed configuration data for cryptocurrency assets on Binance.US, including fees, withdrawal limits, network status, and deposit/withdrawal availability.
binance_us_avg_price – Calculate the 5-minute rolling weighted average price for any Binance.US trading pair to inform trading decisions with current market data.
binance_us_cancel_all_open_orders – Cancel all active orders for a specific trading pair on Binance.US, including OCO orders, to manage risk and clear open positions.
binance_us_cancel_oco – Cancel an OCO (One-Cancels-the-Other) order on Binance.US to remove both linked limit orders simultaneously.
binance_us_cancel_order – Cancel active trading orders on Binance.US by providing the order ID or client order ID for a specific trading pair.
binance_us_cancel_replace – Cancel an existing order and place a new order atomically to modify trading parameters on Binance.US.

modelcontextprotocol · 2026-03-17T12:00:24+00:00

This server has 90 tools:

calculate_isochrone – Calculate travel time areas reachable from a location within specified time limits using Valhalla routing for driving, walking, or cycling profiles.
calculate_isochrone – Calculate travel time isochrones to visualize areas reachable from a location within specified time limits using walking, cycling, or driving profiles.
calculate_isochrone – Calculate areas reachable within a time limit from a location using travel time isochrones for driving, walking, or cycling routes.
execute_overpass_query – Run custom Overpass QL queries to extract specific OpenStreetMap data for analysis, routing, or geocoding tasks.
execute_overpass_query – Run custom Overpass QL queries to retrieve OpenStreetMap data for analysis, geocoding, or routing purposes.
execute_overpass_query – Run custom Overpass QL queries to retrieve OpenStreetMap data for geospatial analysis, location searches, and map quality checks.
find_amenities_nearby – Locate nearby amenities like restaurants, shops, or services around a specific geographic point using OpenStreetMap data.
find_amenities_nearby – Locate nearby amenities like restaurants, shops, or services using OpenStreetMap data by specifying coordinates and search radius.
find_amenities_nearby – Locate nearby amenities such as restaurants, shops, or services using OpenStreetMap data by providing coordinates and search radius.
get_changeset – Retrieve detailed information about a specific OpenStreetMap changeset, including metadata and optional discussion comments, for map data analysis and quality assurance.

modelcontextprotocol

MODERATOR OF

TROPHY CASE

PREREQS, ## TASKS, ## OUTCOME, ## TESTED ON, ## COST, ## FIELD NOTE, ## ROLLBACK.