Integration
Connect Metaview to TensorFeed
When something happens in Metaview, your agent does the next thing in TensorFeed. Describe it and it is built, tested on every scenario and kept running.
What the catalog holds today. Ask for anything missing and your agent reads the API documentation and adds it.
Build solutions, not workarounds.
What do you want Metaview and TensorFeed to do together?
Ask the assistant
Connect your AI client
Give your AI client this address.
https://mcp.apiant.aiAny client that takes a remote MCP server. Nothing to install. Create your free account, then sign in once in your browser.
Set it up in your client
Claude Code
Run this in the directory you want to work in.
claude mcp add --transport http -s project apiant-ai https://mcp.apiant.aiStart Claude Code there, approve the server, and sign in in the browser page it opens.
Claude Code guide (opens in a new tab)Claude, web and desktop
Open Customize, then Connectors, then Add custom connector, and paste the address. On Team and Enterprise an owner adds it first.
Setup guide (opens in a new tab)Cursor
Add the address to your MCP configuration as a server URL. Cursor signs you in in your browser.
Setup guide (opens in a new tab)Zed
Open Settings, then AI, then MCP Servers, then Add Server, then Add Remote Server.
Setup guide (opens in a new tab)Codex and the ChatGPT desktop app
Open Settings, then MCP servers, then Add server, and choose Streamable HTTP. From the terminal, Codex takes the address with its own add command and then signs you in.
Setup guide (opens in a new tab)Any other MCP client
Paste the address where the client asks for a remote MCP server URL, and name the server apiant-ai where it lets you. APIANT's skills reach the client over the same connection.
Setup guide (opens in a new tab)Example flows
What Metaview can start in TensorFeed
When New Conversation in Metaview
then Buy credits in TensorFeed
Starting points drawn from the triggers and actions in the catalog today. Describe the flow you need, at any depth, and your agent builds it and tests every scenario before it ships.
Everything your agent can do with Metaview and TensorFeed
Triggers and actions 1 trigger · 58 actions
- New Conversation
Triggers when a new conversation is available in Metaview.
- Build chart
Creates a visual chart from conversation data with optional filtering, grouping, and timezone adjustment.
- Check enrichment status
Returns enrichment status and usage metrics for candidate data, with options to scope by person or enrichment type.
- Create AI field
Creates a new AI-powered field that analyzes conversations to answer a custom question, with configurable value type.
- Create report
Builds a report from conversations with filtering, metrics, grouping, and custom field inclusion.
- Fetch candidates
Looks up candidate information by ID, LinkedIn URL, email, or phone number in bulk.
- Find candidate's sequences
Finds which outreach sequences a candidate is enrolled in using their ID, LinkedIn URL, email, or phone.
- Get note template
Returns a note generation template by ID for use in automating note creation.
- Get search details
Retrieves configuration and results for a sourcing search by ID.
- Get sourcing analytics
Returns sourcing analytics and metrics grouped by user, search, or date range with filtering options.
- Get sourcing messages
Lists outreach messages sent in a sourcing search with pagination support.
- Get User Context
Returns information about the connected user account and available features.
- Give sourcing feedback
Submits feedback on candidates from a sourcing search, optionally linking to the search that sourced them.
- Group conversations
Groups recorded conversations by a field (like recruiter, stage, or outcome) and returns counts and metrics per group.
- List application reviews
Returns a list of application reviews, optionally filtering by name or showing only active ones.
- List ATS jobs
Returns ATS job postings, optionally filtered by job title.
- List ATS stages
Returns hiring pipeline stages for a job, or workspace-level stages if no job is specified.
- List available fields
Returns available data fields for reports, optionally filtered by name.
- List candidates in sequence
Returns candidates enrolled in a sequence, with optional enrollment status and per-step delivery details.
- List field values
Returns distinct values for a field across conversations, useful for building filters or dropdowns.
- List mailboxes
Returns email mailboxes available in this Metaview workspace.
- List note template folders
Returns folders of note templates organized in the workspace.
- List note templates
Returns note templates available in the workspace, optionally filtered by name or with full section details.
- List sequences
Returns candidate sequences, optionally filtered by name, creator, or status; includes full configuration if requested.
- List sourcing candidates
Returns candidates from a specified sourcing search with optional filtering by pack, feedback status, and detail level.
- List sourcing searches
Returns all sourcing searches with optional pagination.
- Manage candidate sequence
Adds, pauses, resumes, cancels, removes, or updates candidate enrollments in a recruitment sequence.
- Manage note template
Creates, updates, or deletes call note templates with customizable sections for structured note-taking.
- Manage sequence
Creates, updates, duplicates, or deletes recruitment sequences.
- Search conversations
Searches call conversations with optional filtering, sorting, and field selection.
- Search reports
Searches reports by name, category, or ID with optional full configuration details.
- Send sourcing message
Starts or continues a sourcing or research search with a message to the AI agent.
- Buy credits
Initiate a credit purchase against a sender wallet.
- Find AI news
Full-text search across the AI news archive.
- Get AFTA adopter directory
Fetch the machine-readable AFTA adopter directory.
- Get AI agent directory
Fetch a curated directory of AI agents and frameworks.
- Get AI benchmark scores
Fetch public benchmark scores for major AI models.
- Get AI ecosystem daily brief
Fetch a composite daily brief covering the AI ecosystem.
- Get AI model pricing and specs
Fetch pricing and specs for AI models.
- Get AI news
Fetch aggregated AI news articles.
- Get AI podcast episodes
Fetch recent AI podcast episodes.
- Get AI service status
Fetch operational status for major AI services.
- Get benchmark trust verdict
Fetch a trust band and score for an AI benchmark.
- Get cheapest GPU offer
Fetch the cheapest current offer for a canonical GPU.
- Get cross-provider model catalog
Fetch a cross-provider AI model catalog snapshot from OpenRouter.
- Get failover verdict
Fetch the best operational failover target when a provider degrades.
- Get GPU rental pricing
Fetch current GPU rental pricing snapshot.
- Get HF daily papers
Fetch Hugging Face Daily Papers with community signal.
- Get historical snapshot
Fetch one historical daily snapshot by date and type.
- Get hot AI GitHub issues
Fetch currently-hot GitHub issues across AI repos.
- Get LLM endpoint latency probes
Fetch the last 24 hours of LLM endpoint latency probes.
- Get MCP server registry snapshot
Fetch a daily summary of the MCP server registry.
- Get model deprecation calendar
Fetch the AI model deprecation calendar.
- Get recent arXiv papers
Fetch the most recent AI/ML arXiv submissions.
- Get stack safety verdict
Fetch a GO/HOLD/BLOCK deploy gate verdict for an AI-stack package.
- Get trending AI GitHub repos
Fetch trending GitHub repositories in AI.
- Get trending AI papers
Fetch daily citation-ranked AI/ML papers from Semantic Scholar.
- Get trending Hugging Face models
Fetch top trending Hugging Face models, datasets, and Spaces.
- Get trending Reddit AI threads
Fetch currently-hot AI discussion threads on Reddit.
No trigger or action matches that. Ask your agent to add it: it reads the API documentation and builds what you describe.
Each app on its own
Reviews
What our customers say
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Questions
Metaview and TensorFeed, answered
What can start an automation from Metaview?
Any of Metaview's 1 trigger in the catalog, including New Conversation. Describe the moment in plain language and your agent picks the right one.
What can your agent do in TensorFeed when something happens in Metaview?
Any of TensorFeed's 27 actions, including Buy credits, Find AI news, Get AFTA adopter directory and Get AI agent directory. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from TensorFeed to Metaview?
TensorFeed has no triggers in the catalog today, so automations start in Metaview. If you need the other direction, ask: your agent reads TensorFeed's API documentation and adds it.
Do I have to build a connector for Metaview or TensorFeed?
No. Both are in the catalog with their triggers and actions. You describe the automation; your agent builds it, tests every scenario and keeps it running.
What happens when something fails?
Your agent works that out for you. It plans the failure paths along with the happy path, then tests every scenario before it ships.
Is there a free plan?
Yes. Every plan includes the agent, including free, and building from your own AI client spends no assistant credits.