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Retrieves the interactions between the query proteins. Use this method only when you specifically need to list the interactions between all proteins in your query set. If user asks for 'physical' or 'complex' use 'physical' network type. - For a **single protein**, the network includes that protein and its top 10 most likely interaction partners, plus all interactions among those partners. - For **multiple proteins**, the network includes all direct interactions between them. - If the user refers to "physical interactions", "complexes", or "binding", set the network type to "physical". - STRING does not store or report information about self-interactions/homomers; if asked, explain the limitation. If few or no interactions are returned, consider reducing the `required_score`. For large query sets (>50 proteins), consider increasing the `required_score` (e.g. ≥700) to focus on high-confidence interactions and avoid overly dense networks. - Expand the names of score sources: `nscore` (neighborhood), `fscore` (fusion), `pscore` (phylogenetic profile), `ascore` (coexpression), `escore` (experimental), `dscore` (database), `tscore` (text-mining)

Retrieves all interaction partners for one or more proteins from STRING. This tool returns all known interactions between your query protein(s) and **any other proteins in the STRING database**. - Use this when asking **“What does TP53 interact with?”** - It differs from the `network` tool, which only shows interactions **within the input set** or a limited extension of it. - If the user refers to "physical interactions", "complexes", or "binding", set the network type to "physical". You can filter for strong interactions using `required_score`. - Evidence scores: `nscore` (neighborhood), `fscore` (fusion), `pscore` (phylogenetic profile), `ascore` (coexpression), `escore` (experimental), `dscore` (database), `tscore` (text mining)

Creates a downloadable file for STRING-derived results. Use this tool when the user explicitly asks to download, save, export, or receive a file containing STRING data, tables, protein lists, enrichment results, networks, etc. When a response would otherwise include a publication-style or supplementary result table, or another table clearly intended for reuse outside chat, mention that a downloadable TSV/CSV file can be generated on request. Ask whether they want the file, unless they already requested it. Do not create the file until the user asks for it. Do not store unrelated data or full conversation transcripts.

Create a new container image build from a Git repository or Dockerfile.

Search fish and aquatic animal profiles in the Atlarium habitat database.

Get a structured fish or aquatic animal profile from the Atlarium habitat database.

Get a structured aquatic plant profile.

Get a structured public habitat product profile.

Search public algae diagnostic profiles with symptoms, causes and treatment guidance.

Get a structured public algae diagnostic profile.

Deploy a v2 app: an HTML document + a capability manifest, hosted at its own URL. The manifest has eight extension keys: app metadata; collections (+ per-collection write/update/read/delete role lists, where write gates creates and also updates unless the optional update list is declared; declare update:["creator"] on any collection whose rows belong to one person, or every caller admitted by write can overwrite every row); externalHosts (fetch allowlist); cdn (allow CDN scripts/styles); capabilities (Permissions-Policy opt-ins); embeds (iframe frame-src allowlist); notify (email-on-row rules); webhooks (signed HTTP POST on-row rules). Pass EITHER no `app_id` (create, mints a slug + URL) OR `app_id` (redeploy an existing app with new content). Supply the HTML as INLINE `html` OR as `html_path` (an absolute path read on the MCP-SERVER host, which is the relay for a hosted connector or your CLI host for a locally-run one, NOT the remote agent's machine; use it to avoid retransmitting a large HTML file every deploy, but only a locally-run connector can read it, and if both are given inline `html` wins). Pass `dry_run:true` (alias `check`) to VALIDATE ONLY: it runs the full manifest + asset-shape validation, the redeploy compat gate, and the schedule-timezone advisory, then returns { ok, warnings, compat?, breaks? } WITHOUT creating a version or mutating anything. A redeploy is refused with manifest_incompatible_redeploy (unless force:true) when it would strand rows already written (drops a collection, tightens a schema, flips appendOnly) or when it would WIDEN what the app's install screen discloses (some collection reaching further than the live manifest, e.g. read going to ["anyone"]); the break quotes the sentence a user would now be asked to approve. Taking access away never asks: dropping a role, or adding update:["creator"] to a write:["anyone"] collection, redeploys clean. A removed collection is detached, never deleted. Ship images/fonts/audio/video/data FILES with the app in the SAME call via `assets[]`: each is validated + stored app-scoped and served at its `path` on the app's own origin, so the HTML references it by a stable same-origin path (`<img src="frames/000.jpg">`, `<video src="media/clip.mp4">`), media and font paths support HTTP Range for seeking. A redeploy's assets replace the previous version's set. BEFORE authoring: call get_skill for the manifest grammar. Returns { app_id, slug, url, version, visibility, created } (create) or { app_id, version, compat, breaks? } (redeploy).

Binary attachments (images, PDFs, audio, video) referenced from event payloads / input_data via `format: homespun-attachment-id`. ONE tool with an `action` enum: upload | fetch | presign | finalize | download | show | list | delete | mint_token | revoke_token | list_tokens. TOKEN COST, READ FIRST: an inline `upload` with `content_base64` carries the bytes in the tool-call arguments, so they enter the MODEL CONTEXT and cost tokens PROPORTIONAL TO FILE SIZE (a few-hundred-KB image is already very costly, worse on every retry). For ANY real image or media (anything beyond a tiny icon) use a ZERO-CONTEXT path instead: `fetch` when you have a URL (the relay downloads it server-side, you send only the URL string), or presign + finalize when the client can PUT the raw bytes out-of-band. fetch: { source_url (https), scope } — the relay downloads the URL itself behind an SSRF guard (https only, no private/loopback/metadata hosts, DNS pinned, redirects refused, size-capped, timed out) and runs the same byte-sniff + allowlist + size + quota + scan checks as any upload; works on any storage backend. upload (inline) takes EITHER `content_base64` (base64 bytes, no filesystem; last-resort for small assets or clients with neither a URL nor an out-of-band PUT) OR `file_path` (ABSOLUTE path read on the RELAY host, only usable when the file is local to the relay). presign + finalize (token-free, for images/video/big audio): (1) presign with { mime, size, sha256, scope } returns { put_url, attachment_id }; (2) YOU PUT the raw bytes to put_url over plain HTTP out-of-band; (3) finalize with the attachment_id. At finalize the relay re-reads the stored bytes, BYTE-SNIFFS the real type, and enforces the same allowlist + size + sha256 + quota + scan checks as any upload, so a presign that lies about its mime is caught and never served inline. The presigned path requires the Azure storage backend; a filesystem self-host returns a clear not-supported error (use fetch or inline upload there). download writes to an ABSOLUTE out_path (or returns base64). Scope an upload to agent (default, reusable) or app. mint_token returns a /b/<token> capability URL (ONCE) a browser can GET without your API key.

Agent identity + binding. ONE tool with an `action` enum: whoami (the resolved relay URL, active profile, whether a key is configured — no network, no secrets) | claim (bind this agent to a human via a one-shot claim code from their Settings UI; one-way) | logout (clear the locally-saved key/profile; does NOT revoke it on the relay — use the `key` tool's revoke for that).

Manage YOUR community publisher identity: the @-handle and public profile you present in the template gallery. ONE tool with an `action` enum: claim | get | update. get returns your profile (handle, whether it is claimed yet, tenure, and the rating/template counters). claim sets your handle exactly ONCE (it is permanent afterwards) from a lowercase 3-to-32-char string; a handle that is reserved (platform or role words) or already taken is refused. update changes your public display_name, bio, or url at any time. claim and update require a verified email; an existing publisher may already have a provisional `maker-...` handle (auto-assigned) that claim renames the one allowed time.

Create a new project on sota.io. Each project automatically provisions: (1) a managed PostgreSQL 17 database accessible via the DATABASE_URL environment variable (auto-injected, no configuration needed), (2) PgBouncer connection pooling (pool size 20, max 100 clients), (3) automatic daily database backups with 7-day retention, (4) a live URL at https://{slug}.sota.io with automatic HTTPS via Let's Encrypt. The project slug is auto-generated from the name (lowercase, hyphens, max 63 chars) and is immutable after creation. Supported frameworks: Next.js, Node.js (Express/Fastify/Koa), Python (Flask/FastAPI/Django), or any language via custom Dockerfile. You can also add up to 5 custom domains per project with automatic HTTPS (via API: POST /v1/projects/:id/domains with {domain: "yourdomain.com"}). DNS: A record to 23.88.45.28 for apex domains, CNAME to {slug}.sota.io for subdomains. Optionally associate the project with a public git repository at create-time by passing `git_url` (and optional `git_branch`). The association is informational — it shows up in the dashboard and the `sota deploy --git` CLI flag can default to it — but does NOT enable auto-deploy-on-push yet.

Deploy an application to sota.io. The platform auto-detects your framework and builds a Docker image automatically: - Next.js: Detected via next.config.js/ts. Add output: 'standalone' to next.config for optimal builds. - Node.js: Detected via package.json with a "start" script. Works with Express, Fastify, Koa, Hapi, etc. - Python: Detected via requirements.txt or pyproject.toml. Works with Flask, FastAPI, Django. - Custom Dockerfile: If a Dockerfile exists in the project root, it takes priority over auto-detection. Use this for Go, Rust, Java, or any other language. The EXPOSE directive in the Dockerfile is used to detect the app port automatically. THREE WAYS to supply the source code — pick EXACTLY ONE: 1. **files** (inline source from AI): Pass a map of relative paths to UTF-8 text content. Best when you've just generated a small app in this conversation and want to deploy it without any filesystem step. Up to 200 files, 10 MB total. Include the framework manifest (package.json, requirements.txt, or Dockerfile) so auto-detection works. 2. **git_url** (clone a public repo): Pass an https://, git://, ssh://, or git@host:path URL. We shallow-clone it (--depth=1 --single-branch) on the server and deploy. Optional git_branch picks a non-default branch. Only public repos are supported in v1. Max 200 MB after clone. 3. **directory** (local filesystem): Pass an absolute path. Only works when the MCP client has filesystem access (Claude Code / CLI; not Claude.ai web). Defaults to the current working directory when omitted. IMPORTANT: Your app MUST listen on the PORT environment variable. For auto-detected frameworks (Next.js, Node.js, Python) PORT is 8080. For custom Dockerfiles, the port is auto-detected from the EXPOSE directive (e.g. EXPOSE 3000 sets PORT=3000). If no EXPOSE is found, it defaults to 8080. Every project includes a managed PostgreSQL 17 database. Six environment variables are auto-injected into your container — no manual database configuration needed: DATABASE_URL (full connection string), PGHOST, PGPORT, PGUSER, PGPASSWORD, and PGDATABASE. Libraries that follow libpq conventions (node-postgres, pgx, psycopg2, Django) pick up the PG* variables automatically with no configuration. If your app needs database migrations, run them on startup. Deployments use blue-green strategy for zero downtime. The old container keeps running until the new one passes health checks (60s timeout). Use get-logs to monitor build progress. Files matching .gitignore, .git/, node_modules/, .env, and .DS_Store are excluded from the archive.

Get build and runtime logs for a deployment. If no deployment_id is provided, returns logs for the latest deployment. Use this after calling deploy to monitor build progress and diagnose failures. Logs include: framework detection output, dependency installation, build steps, container startup, and health check results. If a deployment fails, check the logs for error details — common issues include missing dependencies, build errors, or the app not listening on the correct PORT (check the PORT env var — 8080 for auto-detected frameworks, or the EXPOSE value from Dockerfile).

Set an environment variable for a project. Variables are encrypted at rest (AES-256-GCM) and injected at container runtime. NOTE: DATABASE_URL, PGHOST, PGPORT, PGUSER, PGPASSWORD, and PGDATABASE are all auto-injected for the managed PostgreSQL database — you do NOT need to set any of them manually. The PORT variable is auto-managed: 8080 for auto-detected frameworks (Next.js, Node.js, Python), or auto-detected from the Dockerfile EXPOSE directive for custom Dockerfile builds. IMPORTANT: Changing env vars does NOT auto-redeploy. You must call deploy or use the redeploy API endpoint to apply changes. For Next.js apps, NEXT_PUBLIC_* variables must be set BEFORE deploying since they are embedded at build time.

Read a file from the agent workspace by path (e.g. ./notes.md, /etc/...).

"Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO, news, GLEIF and returns: cik + company_name; recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. Pass ticker "AAPL" or zero-padded CIK "0000320193" — names not supported (use resolve_entity first if you only have a name).

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since `since`), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). `since` accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

What can I ask Pipeworx? / what is Pipeworx good for? / what can you do? / give me ideas / show me examples / getting started / what data do you have? — the onboarding entry point for an agent that just connected and wants to know what is worth asking. Returns category-bucketed example questions (company financials, drugs & clinical trials, economics, real estate, prediction markets, weather, government & patents, science & academia, news) — each with the exact tool + argument shape that answers it, drawn from the live catalog of thousands of tools. Call with no arguments for the full spread, or pass `topic` (e.g. "finance", "pharma", "betting") to focus. Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools (ask_pipeworx, entity_profile, compare_entities, etc.).

Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

"Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO, news, GLEIF and returns: cik + company_name; recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. Pass ticker "AAPL" or zero-padded CIK "0000320193" — names not supported (use resolve_entity first if you only have a name).

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since `since`), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). `since` accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

What can I ask Pipeworx? / what is Pipeworx good for? / what can you do? / give me ideas / show me examples / getting started / what data do you have? — the onboarding entry point for an agent that just connected and wants to know what is worth asking. Returns category-bucketed example questions (company financials, drugs & clinical trials, economics, real estate, prediction markets, weather, government & patents, science & academia, news) — each with the exact tool + argument shape that answers it, drawn from the live catalog of thousands of tools. Call with no arguments for the full spread, or pass `topic` (e.g. "finance", "pharma", "betting") to focus. Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools (ask_pipeworx, entity_profile, compare_entities, etc.).

Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

Publish files to the web → live URL at <slug>.shiply.now. UPDATING: never create a new site for changes — re-call with claimToken (anonymous sites) or slug (sites you own with a Bearer key) and the SAME URL gets the new version. Unchanged files are hash-skipped server-side, so re-publishing (including retrying a failed publish) is cheap — always update the same site rather than creating a new one. Works WITHOUT auth (anonymous: 24h lifetime, returns claimToken/claimUrl — SAVE THEM). With a Bearer shp_ key sites are permanent. ≤50 files / 2 MB inline; bigger: REST flow per https://shiply.now/llms.txt. index.html serves at /. spaMode for client-side routing.

PERMANENTLY delete a site and all stored files. Irreversible — confirm with the user first.

List a site's finalized deploys newest-first (id, createdAt, isLive, fileCount, bytes), capped at 20. Pair with rollback_site: pick a version id from here and re-point the site to it.

Download the current files of a site you own (or created via a platform connection) so you can edit and republish to the same slug with publish_site. Static sites return editable source; framework/SSR sites return the built bundle (`.shiply/bundle/*`), not original source.

Give ONE site a vanity URL: rename it to <handle>.shiply.now (3-30 chars, a-z 0-9 -). The old address 301-redirects for 30 days. (For a portfolio page listing all your sites, use set_profile instead — that lives at shiply.now/@<handle>.)

Server-side copy of an owned site under a new slug — instantly live. Copies files + title; does NOT copy access settings, domains, or data. Great for iterating on variants.

数据画像：每列类型/去重近似数/空值率 + 数值列 min/max/avg/std/分位数（1 credit/次）。 相当于 pandas df.describe()——AI 拿它一眼看清整份数据的分布与质量。失败自动退款。 返回 {ok, format, n_rows, n_cols, profile[]}。

Retrieve the source code of a specific exploit by its platform ID. IMPORTANT: Use the platform's internal ID shown as [id=XXXXX] in results, NOT the ExploitDB number (EDB-XXXXX). These are different numbering systems. Returns code from the exploit archive. If no file_path is specified, auto-selects the most relevant code file. Use this to analyze exploit mechanics, understand attack techniques, or review PoC code.

Get an exploit author's profile with all their exploits. Returns author name, handle, total exploit count, activity start date, and a paginated list of their exploits with CVE context. Use this when asked about a specific researcher like 'show me all exploits by Chocapikk'.

Import data into a Cloud SQL instance. If the file doesn't start with `gs://`, then the assumption is that the file is stored locally. If the file is local, then the file must be uploaded to Cloud Storage before you can make the actual `import_data` call. To upload the file to Cloud Storage, you can use the `gcloud` or `gsutil` commands. Before you upload the file to Cloud Storage, consider whether you want to use an existing bucket or create a new bucket in the provided project. After the file is uploaded to Cloud Storage, the instance service account must have sufficient permissions to read the uploaded file from the Cloud Storage bucket. This can be accomplished as follows: 1. Use the `get_instance` tool to get the email address of the instance service account. From the output of the tool, get the value of the `serviceAccountEmailAddress` field. 2. Grant the instance service account the `storage.objectAdmin` role on the provided Cloud Storage bucket. Use a command like `gcloud storage buckets add-iam-policy-binding` or a request to the Cloud Storage API. It can take from two to up to seven minutes or more for the role to be granted and the permissions to be propagated to the service account in Cloud Storage. If you encounter a permissions error after updatingthe IAM policy, then wait a few minutes and try again. After permissions are granted, you can import the data. We recommend that you leave optional parameters empty and use the system defaults. The file type can typically be determined by the file extension. For example, if the file is a SQL file, `.sql` or `.csv` for CSV file. The following is a sample SQL `importContext` for MySQL. ``` { "uri": "gs://sample-gcs-bucket/sample-file.sql", "kind": "sql#importContext", "fileType": "SQL" } ``` There is no `database` parameter present for MySQL since the database name is expected to be present in the SQL file. Specify only one URI. No other fields are required outside of `importContext`. For PostgreSQL, the `database` field is required. The following is a sample PostgreSQL `importContext` with the `database` field specified. ``` { "uri": "gs://sample-gcs-bucket/sample-file.sql", "kind": "sql#importContext", "fileType": "SQL", "database": "sample-db" } ``` The `import_data` tool returns a long-running operation. Use the `get_operation` tool to poll its status until the operation completes.