"github" matching MCP tools:

• entity_profile

  github

  Get everything about a company in one call. Use when a user asks "tell me about X", "give me a profile of Acme", "what do you know about Apple", "research Microsoft", "brief me on Tesla", or you'd otherwise need to call 10+ pack tools across SEC EDGAR, SEC XBRL, USPTO, news, and GLEIF. Returns recent SEC filings, latest revenue/net income/cash position fundamentals, USPTO patents matched by assignee, recent news mentions, and the LEI (legal entity identifier) — all with pipeworx:// citation URIs. Pass a ticker like "AAPL" or zero-padded CIK like "0000320193".

  Connector

• ateam_build_and_run

  ateam-mcp

  Build and deploy a governed AI Team solution in one step. ⚠️ HEAVIEST OPERATION (60-180s): validates solution+skills → deploys all connectors+skills to A-Team Core (regenerates MCP servers) → health-checks → optionally runs a warm test → auto-pushes to GitHub. AUTO-DETECTS GitHub repo: if you omit mcp_store and a repo exists, connector code is pulled from GitHub automatically. First deploy requires mcp_store. After that, write files via ateam_github_write, then just call build_and_run without mcp_store. For small changes to an already-deployed solution, prefer ateam_patch (faster, incremental). Requires authentication.

  Connector

• scaffold_pipeline_workflow

  Keploy

  Generate the exact CI workflow YAML to add keploy sandbox tests to a pull-request pipeline, and tell you where to write it. Use this when the dev asks to "add keploy sandbox tests to my pipeline" / "wire keploy into CI" / "run keploy on PR" / "add a CI job for keploy" — the server emits the file contents verbatim so you don't have to compose the flag list yourself. ===== GOAL ===== Write a CI workflow file that runs `keploy test sandbox --cloud-app-id <uuid> --app-url <url>` on pull requests and gates the PR on the result. NEVER kick off an actual test run in this flow — it is pure file authoring, ends with the file on disk. DO NOT fire replay_sandbox_test, record_sandbox_test, replay_test_suite, or any other run-starting MCP tool here. ===== HOW (absolute) ===== Call this tool. It returns { file_path, content, summary }. Write the "content" to "file_path" VERBATIM via your Write tool — NO flag renames, NO flag removals, NO step reordering, NO synthesis. The server owns the YAML template; your job is only to (1) resolve the inputs from the repo and api-server and (2) Write the returned content. Do NOT compose the YAML yourself from general knowledge — flag drift (missing --cloud-app-id, inventing --app) is the most common bug when Claude improvises. DO NOT ASK the dev for confirmation before writing. Resolve everything from the repo + api-server, pick the GitHub Actions default, call this tool, Write the file. The dev's prompt is already the go-ahead. ===== STEPS ===== 1. DETECT THE CI SYSTEM: * Default = GitHub Actions (biggest share). File = .github/workflows/keploy-sandbox.yml. * If .gitlab-ci.yml exists → GitLab (not yet supported by this tool; tell the dev and stop). * If .circleci/config.yml exists → Circle (not yet supported; tell the dev and stop). * Otherwise → GitHub Actions. 2. RESOLVE VALUES by calling MCP tools + reading the repo: * app_id: call listApps({q: "<cwd basename>"}). Exactly one → use its id. Multiple → pick the one whose name most specifically matches the repo's primary service (e.g. "orderflow.producer" wins over "orderflow" when there's a ./producer directory); mention which you picked in the final message. Zero → stop and tell the dev to create the app + rerecord first. * suite_ids: DO NOT pass this arg by default. An empty suite_ids means the CLI resolves "every linked sandbox suite for the app" at CI run time — which is what you want (new suites auto-pick up without workflow edits). The tool still verifies there's ≥1 linked suite at scaffold time so the first PR run doesn't fail empty-handed. Only pass suite_ids when the dev explicitly narrows ("run only the auth suite in CI"); don't pin "all current suites" — that's staleness waiting to happen. * compose_file: READ THE REPO. Default is docker-compose.yml. AVOID passing a docker-compose-keploy.yaml variant that has `networks: default: external: true` — those variants only work locally, where another compose run has already created the external network. In CI the runner starts clean and `external: true` fails with "network not found". If the primary docker-compose.yml brings up the full app (deps + app service), use it end-to-end. * app_service, container_name, app_port: read from the SAME compose_file you picked above. app_service = the service key (e.g. "producer"); container_name = that service's container_name: field in that same compose file (e.g. "orderflow-producer" if compose_file=docker-compose.yml, but "producer" if compose_file=docker-compose-keploy.yaml — THESE DIFFER, pick consistently); app_port = the host-side of its ports: mapping. * app_url = http://localhost:<app_port>. The tool derives this; you don't pass it separately. 3. CALL THIS TOOL with app_id, app_service, container_name, app_port, compose_file (and suite_ids only if the dev explicitly narrowed scope). It returns { file_path, content, summary }. Write the "content" to the "file_path" VERBATIM. ===== FLAG NAME RULES (absolute, do not drift when reviewing the output) ===== * `--cloud-app-id` ← NOT `--app-id`. The OSS config has an `appId` uint64 field that viper maps `--app-id` into; passing a UUID there fails with "invalid syntax" before RunE runs. * `keploy test sandbox --cloud-app-id <uuid> --app-url <url>` ← the CI form. NOT `keploy test --cloud-app-id` (must be `test sandbox` — the headless flags live on the sandbox subcommand only), NOT `keploy test-suite run` (that command doesn't exist). There is NO `--pipeline` flag. * Install URL = `https://keploy.io/ent/install.sh` ← NOT `https://keploy.io/install.sh` (OSS; no sandbox subcommand at all), NOT a github.com/keploy/keploy release tarball. If the server-emitted content ever disagrees with these rules, trust the server output and file a bug — don't edit the YAML. ===== RESOLUTION ARGS ===== * Pass either app_id (explicit UUID) or app_name_hint (substring; server does listApps and requires exactly one match). * Pass app_service (docker-compose service name), container_name (from compose container_name: field read from the SAME compose_file arg), and app_port (HTTP port the service exposes). * compose_file is optional, defaults to "docker-compose.yml". If the repo has a -keploy.yaml variant with `external: true` networks, do NOT point compose_file at it — it won't work in CI. * suite_ids is optional and should be LEFT BLANK by default — the CLI resolves every linked suite at run time. Only pin an explicit list when the dev narrows scope. ===== FINAL RESPONSE — three short sections, no questions ===== ### Created | File | Lines | | --- | --- | | .github/workflows/keploy-sandbox.yml | N | ### Summary - App: <name> (<app_id>), <N> linked suites replayed on every PR - Trigger: pull_request → main, + manual workflow_dispatch - Failure on any suite gates the PR (non-zero exit from the CLI) ### Before the first run, add this GitHub secret - `KEPLOY_API_KEY` — at https://github.com/<owner>/<repo>/settings/secrets/actions/new (self-hosted users — point at your own api-server by building the enterprise binary with -X main.api_server_uri=<url>; there is no runtime env override on the released binary.) This tool does NOT run anything. It only generates file contents.

  Connector

• aws___read_documentation

  AWS Knowledge

  Fetch and convert AWS related documentation pages to markdown format. ## Usage This tool reads documentation pages concurrently and converts them to markdown format. Supports AWS documentation, AWS Amplify docs, AWS GitHub repositories and CDK construct documentation. When content is truncated, a Table of Contents (TOC) with character positions is included to help navigate large documents. ## Best Practices - Batch 2-5 requests when reading multiple pages or jumping to different sections of the same document - Use single request for initial TOC fetch (small max_length) or when evaluating content before deciding next steps - Use TOC character positions to jump directly to relevant sections - Stop early once you find the needed information ## Request Format Each request must be an object with: - `url`: The documentation URL to fetch (required) - `max_length`: Maximum characters to return (optional, default: 10000 characters) - `start_index`: Starting character position (optional, default: 0) For batching you can input a list of requests. ## Example Request ``` { "requests": [ { "url": "https://docs.aws.amazon.com/AmazonS3/latest/userguide/access-management.html", "max_length": 5000, "start_index": 0 }, { "url": "https://repost.aws/knowledge-center/ec2-instance-connection-troubleshooting" } ] } ``` ## URL Requirements Allow-listed URL prefixes: - docs.aws.amazon.com - aws.amazon.com - repost.aws/knowledge-center - docs.amplify.aws - ui.docs.amplify.aws - github.com/aws-cloudformation/aws-cloudformation-templates - github.com/aws-samples/aws-cdk-examples - github.com/aws-samples/generative-ai-cdk-constructs-samples - github.com/aws-samples/serverless-patterns - github.com/awsdocs/aws-cdk-guide - github.com/awslabs/aws-solutions-constructs - github.com/cdklabs/cdk-nag - constructs.dev/packages/@aws-cdk-containers - constructs.dev/packages/@aws-cdk - constructs.dev/packages/@cdk-cloudformation - constructs.dev/packages/aws-analytics-reference-architecture - constructs.dev/packages/aws-cdk-lib - constructs.dev/packages/cdk-amazon-chime-resources - constructs.dev/packages/cdk-aws-lambda-powertools-layer - constructs.dev/packages/cdk-ecr-deployment - constructs.dev/packages/cdk-lambda-powertools-python-layer - constructs.dev/packages/cdk-serverless-clamscan - constructs.dev/packages/cdk8s - constructs.dev/packages/cdk8s-plus-33 - strandsagents.com/ Deny-listed URL prefixes: - aws.amazon.com/marketplace ## Example URLs - https://docs.aws.amazon.com/AmazonS3/latest/userguide/bucketnamingrules.html - https://docs.aws.amazon.com/lambda/latest/dg/lambda-invocation.html - https://aws.amazon.com/about-aws/whats-new/2023/02/aws-telco-network-builder/ - https://aws.amazon.com/builders-library/ensuring-rollback-safety-during-deployments/ - https://aws.amazon.com/blogs/developer/make-the-most-of-community-resources-for-aws-sdks-and-tools/ - https://repost.aws/knowledge-center/example-article - https://docs.amplify.aws/react/build-a-backend/auth/ - https://ui.docs.amplify.aws/angular/connected-components/authenticator - https://github.com/aws-samples/aws-cdk-examples/blob/main/README.md - https://github.com/awslabs/aws-solutions-constructs/blob/main/README.md - https://constructs.dev/packages/aws-cdk-lib/v/2.229.1?submodule=aws_lambda&lang=typescript - https://github.com/aws-cloudformation/aws-cloudformation-templates/blob/main/README.md - https://strandsagents.com/docs/user-guide/quickstart/overview/index.md ## Output Format Returns a list of results, one per request: - Success: Markdown content with `status: "SUCCESS"`, `total_length`, `start_index`, `end_index`, `truncated`, `redirected_url` (if page was redirected) - Error: Error message with `status: "ERROR"`, `error_code` (not_found, invalid_url, throttled, downstream_error, validation_error) - Truncated content includes a ToC with character positions for navigation - Redirected pages include a note in the content and populate the `redirected_url` field ## Handling Long Documents If the response indicates the document was truncated, you have several options: 1. **Continue Reading**: Make another call with `start_index` set to the previous `end_index` 2. **Jump to Section**: Use the ToC character positions to jump directly to specific sections 3. **Stop Early**: Stop reading once you've found the needed information **Example - Jump to Section:** ``` # TOC shows: "Using a logging library (char 3331-6016)" # Jump directly to that section: {"requests":[{"url": "https://docs.aws.amazon.com/lambda/latest/dg/python-logging.html", "start_index": 3331, "max_length": 3000}]} ```

  Connector

• tf_premium_agent_context

  terminalfeed

  The "always start here" premium call for autonomous agents. Composes 13 upstream sources into a curated world-state snapshot: BTC ticker, Fear and Greed, VIX, Fed funds rate, USD-base forex (EUR/JPY/GBP/CHF), HN front page top 5, significant earthquakes 24h, upcoming space launches, top Polymarket markets, and infrastructure status (GitHub, Cloudflare, OpenAI, Anthropic). Returns BOTH a structured JSON `context` object for parsers AND a pre-formatted `system_prompt` string (~350 tokens) the agent pastes verbatim into its LLM context. Saves the agent from making 13 separate calls and writing a formatter. Curation choice (which signals matter, how to compress them) is the moat. Costs 2 credits ($0.04 USDC). 5-min cache. Bearer auth required.

  Connector

• scan_skill

  SecurityScan

  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

• update_doc

  Dock

  Replace a workspace's doc body. Takes EITHER TipTap JSON (`content`) OR Markdown (`markdown`): pass markdown when you're producing prose from scratch (CommonMark + GFM is the format every LLM emits natively), pass TipTap JSON when you need structural edits to an existing doc (round-trip from get_doc, mutate, write back). Beyond CommonMark + GFM, the markdown layer recognizes: - **```mermaid** fenced code → diagram (15 sub-types: flowchart, sequence, gantt, ER, state, class, mindmap, timeline, pie, quadrant, sankey, XY-chart, packet, block, journey) - **$x$** inline math, **$$x$$** block math (LaTeX, KaTeX-rendered, scripts/href disabled) - **> [!NOTE]** / **[!TIP]** / **[!IMPORTANT]** / **[!WARNING]** / **[!CAUTION]** GFM-style callouts - **```svg** fenced code → sanitized SVG embed (the universal escape hatch for custom diagrams; scripts and event handlers stripped at write time) - **<details><summary>X</summary>BODY</details>** → collapsible toggle - **[[slug]]** / **[[org/slug]]** / **[[slug#tab]]** / **[[slug#row-id]]** / **[[slug|display]]** → cross-references to another workspace, surface, or row. Resolved against your accessible workspace set; targets you can't see render as plain text on the reader's side (no info leak). Every cross-ref creates a Backlink row so the target's 'referenced from' sidebar shows this doc. - **[@Label](dock:mention/<kind>/<id>)** → @-mention of a user or agent. `<kind>` is `agent` or `human`; `<id>` is the principal id. Optional query params `?org=<slug>` (agents) or `?email=<addr>` (humans) for renderer hints. Mentioning a human writes a `doc_mention` row to their inbox + sends a deep-link email; mentioning an agent fires the `doc.mention_added` webhook so the agent service can wake up and reply. Re-saving a doc that already mentions someone does NOT re-fire — only newly-added mentions notify (computed from a diff against the previous body). Use this from agent code to ping a teammate when a doc you wrote needs their eyes. - A **lone URL on its own line** from a safelisted provider (YouTube, Vimeo, Loom, Figma, CodePen, GitHub gists) → sandboxed iframe embed. Other URLs stay as regular links. Surrounding prose disqualifies the auto-embed. Per-format caps: max 50 Mermaid diagrams (30 KB source each), max 500 math expressions (8 KB source each), max 50 SVG blocks (100 KB source each post-sanitize), max 200 cross-refs per doc, max 500 @-mentions per doc, max 20 embeds per doc. See /docs/doc-formats for examples. Last-write-wins; no CRDT merge. Emits doc.updated + doc.heading_added + doc.mention_added events as applicable. Requires editor role. Multi-surface workspaces optionally accept `surface_slug` to write to a specific doc tab; omitted writes the primary doc surface. Append-only updates have a dedicated `append_doc_section` tool that doesn't require fetching the body first.

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• deploy_staging

  RationalBloks

  Deploy a project to the staging environment. This triggers: (1) Schema validation, (2) Docker image build, (3) GitHub commit, (4) Kubernetes deployment, (5) Database migrations. The operation is ASYNCHRONOUS - it returns immediately with a job_id. Use get_job_status with the job_id to monitor progress. Deployment typically takes 2-5 minutes depending on schema complexity. If deployment fails, check: (1) Schema format is FLAT (no 'fields' nesting), (2) Every field has a 'type' property, (3) Foreign keys reference existing tables, (4) No PostgreSQL reserved words in table/field names. Use get_project_info to see if the deployment succeeded.

  Connector

• secret_scan

  AgentSec MCP

  Scan text content for hardcoded secrets, API keys, and credentials using 20 pre-compiled patterns. Privacy guarantee: Input text is NEVER logged, cached, stored, or forwarded. Only findings_count and finding offsets (not matched values) are returned. Detected pattern types include: AWS keys, GitHub/GitLab PATs, OpenAI/Anthropic keys, Stripe secrets, Slack tokens, PEM private keys, JWT tokens, and 13 more. Per-call rate limit: 100/min. Payment: $0.05 USDC per scan.

  Connector

• find_examples

  Senzing

  Find working SOURCE CODE examples from 37 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. Returns GitHub raw URLs for file retrieval — fetch to read the source code.

  Connector

• convoopen

  InsideOut (Riley)

  WORKFLOW: Step 1 of 4 - Start infrastructure design conversation Open an InsideOut V2 session and receive the assistant's intro message. The response contains a clean message from Riley (the infrastructure advisor) - display it to the user. ⚠️ Riley will ask questions - forward these to the user, DO NOT answer on their behalf. CRITICAL: This tool returns a session_id in the response metadata. You MUST use this session_id for ALL subsequent tool calls (convoreply, tfgenerate, tfdeploy, etc.). ⚠️ The session_id includes a ?token=... suffix (format: sess_v2_xxx?token=yyy) which is part of the session credential — without it, downstream tools fall back to a tokenless connect URL that 401s. Always pass session_id verbatim to subsequent tools and to the user; do NOT shorten, paraphrase, or strip the ?token= portion when summarizing the session in chat or in your own scratch notes. Use when the user mentions keywords like: 'setup my cloud infra', 'provision infrastructure', 'deploy infra', 'start insideout', 'use insideout', or similar intent to begin infra setup. OPTIONAL: project_context (string) - General tech stack summary so Riley can skip discovery questions and jump to recommendations. The agent should confirm this with the user before sending. Include whichever apply: language/framework, databases/services, container usage, existing IaC, CI/CD platform, cloud provider, Kubernetes usage, what the project does. Example: 'Next.js 14 + TypeScript, PostgreSQL, Redis, Docker Compose, deployed to AWS ECS, GitHub Actions CI/CD, ~50k MAU'. NEVER include credentials, secrets, API keys, PII, source code, or internal URLs/IPs -- only general metadata summaries useful to a cloud architect agent. IMPORTANT: source (string) - You MUST set this to identify which IDE/tool you are. Auto-detect from your environment: 'claude-code', 'codex', 'antigravity', 'kiro', 'vscode', 'web', 'mcp'. If unsure, use the name of your IDE/tool in lowercase. Do NOT omit this — it controls the 'Open {IDE}' button on the credential connect screen. OPTIONAL: github_username (string) - GitHub username for deploy commit attribution. Pre-populates the GitHub username field on the connect page. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.

  Connector

• convoopen

  InsideOut (Riley)

  WORKFLOW: Step 1 of 4 - Start infrastructure design conversation Open an InsideOut V2 session and receive the assistant's intro message. The response contains a clean message from Riley (the infrastructure advisor) - display it to the user. ⚠️ Riley will ask questions - forward these to the user, DO NOT answer on their behalf. CRITICAL: This tool returns a session_id in the response metadata. You MUST use this session_id for ALL subsequent tool calls (convoreply, tfgenerate, tfdeploy, etc.). ⚠️ The session_id includes a ?token=... suffix (format: sess_v2_xxx?token=yyy) which is part of the session credential — without it, downstream tools fall back to a tokenless connect URL that 401s. Always pass session_id verbatim to subsequent tools and to the user; do NOT shorten, paraphrase, or strip the ?token= portion when summarizing the session in chat or in your own scratch notes. Use when the user mentions keywords like: 'setup my cloud infra', 'provision infrastructure', 'deploy infra', 'start insideout', 'use insideout', or similar intent to begin infra setup. OPTIONAL: project_context (string) - General tech stack summary so Riley can skip discovery questions and jump to recommendations. The agent should confirm this with the user before sending. Include whichever apply: language/framework, databases/services, container usage, existing IaC, CI/CD platform, cloud provider, Kubernetes usage, what the project does. Example: 'Next.js 14 + TypeScript, PostgreSQL, Redis, Docker Compose, deployed to AWS ECS, GitHub Actions CI/CD, ~50k MAU'. NEVER include credentials, secrets, API keys, PII, source code, or internal URLs/IPs -- only general metadata summaries useful to a cloud architect agent. IMPORTANT: source (string) - You MUST set this to identify which IDE/tool you are. Auto-detect from your environment: 'claude-code', 'codex', 'antigravity', 'kiro', 'vscode', 'web', 'mcp'. If unsure, use the name of your IDE/tool in lowercase. Do NOT omit this — it controls the 'Open {IDE}' button on the credential connect screen. OPTIONAL: github_username (string) - GitHub username for deploy commit attribution. Pre-populates the GitHub username field on the connect page. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.

  Connector

• create_session

  sncro

  Create a new sncro session. Returns a session key and secret. Args: project_key: The project key from CLAUDE.md (registered at sncro.net) git_user: The current git username (for guest access control). If omitted or empty, the call is treated as a guest session — allowed only when the project owner has "Allow guest access" enabled. brief: If True, skip the first-run briefing (tool list, tips, mobile notes) and return a compact response. Pass this on the second and subsequent create_session calls in the same conversation, once you already know how to use the tools. After calling this, tell the user to paste the enable_url in their browser. Then use the returned session_key and session_secret with all other sncro tools. If no project key is available: tell the user to go to https://www.sncro.net/projects to register their project and get a key. It takes 30 seconds — sign in with GitHub, click "+ Add project", enter the domain, and copy the project key into CLAUDE.md.

  Connector

• setup_payment

  BoostedTravel

  Attach a payment card. Required before booking. For testing: {"token": "tok_visa"} For production: {"payment_method_id": "pm_xxx"} from Stripe.js One-time setup — all future charges are automatic. Requires GitHub star verification.

  Connector

• generate_scaffold

  Senzing

  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. Returns GitHub raw URLs — fetch each snippet to read the source code.

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• calculate_risk_score

  ContrastAPI

  Composite CVE risk score (0-100) — fuses CVSS, EPSS, KEV, and PoC into a single agent-ready triage signal. Formula: CVSS*0.20 + EPSS*0.35 + KEV*0.30 + PoC*0.15 (each component rescaled to 0-100 before weighting). Multiplicative boosters applied in order: KEV+PoC combo (*1.15), critical-severity-with-high-EPSS (CVSS>=9 AND EPSS>0.7, *1.10), recently published (within last 7 days, *1.05). Final score clamped to [0, 100]. Label bands: CRITICAL>=90, HIGH>=70, MEDIUM>=40, LOW<40. Urgency text encodes patch SLA (immediate when KEV; 24h/72h/30d by label). Use to triage a single CVE without orchestrating cve_lookup + exploit_lookup separately. PoC signal here is the local ExploitDB mirror only — for full multi-source exploit detail (GitHub Advisory + Shodan refs + ExploitDB), call exploit_lookup separately. Methodology adapted from mukul975/cve-mcp-server (Apache-2.0): https://github.com/mukul975/cve-mcp-server. Free: 30/hr, Pro: 500/hr. Returns {cve_id, score (0-100), label (CRITICAL/HIGH/MEDIUM/LOW), urgency, has_public_poc, components (cvss_v3, epss_score, in_kev, has_public_poc, weighted_breakdown), boosters_applied, recommendation, summary, verdict, next_calls}.

  Connector

• ateam_github_patch

  ateam-mcp

  Edit a file in the solution's GitHub repo and commit. Two modes: 1. FULL FILE: provide `content` — replaces entire file (good for new files or small files) 2. SEARCH/REPLACE: provide `search` + `replace` — surgical edit without sending full file (preferred for large files like server.js) Always use search/replace for large files (>5KB). Always read the file first with ateam_github_read to get the exact text to search for.

  Connector

• book_flight

  BoostedTravel

  Book an unlocked flight. Creates a real airline PNR with e-ticket. REQUIREMENTS: 1. Offer must be unlocked first (call unlock_flight_offer) 2. Use passenger_id from search results 3. Use REAL passenger details — airline sends e-ticket to the email provided Requires GitHub star verification.

  Connector

• ateam_upload_connector

  ateam-mcp

  Upload connector code to Core and restart — WITHOUT redeploying skills. Use this to update connector source code (server.js, UI assets, plugins) quickly. Set github=true to pull files from the solution's GitHub repo, or pass files directly. Much faster than ateam_build_and_run for connector-only changes.

  Connector

• audit_dependencies

  proof-of-commitment

  Batch-score multiple npm, PyPI, Cargo, or Go packages for supply chain risk. Takes a list of package names and returns a risk table sorted by commitment score (lowest = highest risk first). Risk flags: - CRITICAL: single publisher + >10M weekly downloads (publish-access concentration risk) - HIGH: new package (<1yr) + high downloads (unproven, rapid adoption = supply chain risk) - WARN: low publisher count + high downloads Perfect for auditing a full package.json, requirements.txt, Cargo.toml, or go.mod — paste your dependency list and get a prioritized risk report. For Go: pass full module paths (e.g., "github.com/gin-gonic/gin", "golang.org/x/net") and set ecosystem="golang". The "maintainers" column shows GitHub contributor count since Go has no centralized publisher concept. Examples: score all deps in a project, compare two similar packages, identify abandonware before it becomes a CVE.

  Connector