"PostgreSQL" matching MCP tools:

• sixta_explain_planA

  sixta-connectA

  Turn raw EXPLAIN output into a plain-language diagnosis — no query needed. Paste PostgreSQL EXPLAIN / EXPLAIN ANALYZE (text or JSON) or MySQL EXPLAIN (tabular, \G, FORMAT=JSON, FORMAT=TREE) and get: what the planner is doing step by step, where the cost concentrates, named risk findings (full scans, spilling sorts, nested-loop blowups, row misestimates) with index suggestions, and what to look at next. Use when the user pastes EXPLAIN output or asks 'can you read this plan'. Input is analyzed in memory and never stored.

  ConnectorOAuth

• sixta_explain_errorA

  sixta-connectA

  Decode a database error and get the fix and the next step — no connection needed. Paste a MySQL error number (1213, 1062, 1452, 1205…) or a PostgreSQL SQLSTATE (40P01, 23505, 53300…), optionally with the failing statement, and get the proximate cause, the concrete fix, and — when it helps — the SIXTA tool and artifact to go deeper (e.g. a deadlock → paste SHOW ENGINE INNODB STATUS for sixta_explain_deadlock). Use when the user pastes a DB error code or message. Input is analyzed in memory and never stored.

  ConnectorOAuth

• read_dataA

  QuadraticA

  Read-only queries on the open spreadsheet. No data is modified. Safe to auto-approve. Call as {"action": "<name>", "params": {...}} — per-action params are listed in the Action Reference below. Special actions (not shown in the action enum): • batch — {"action": "batch", "params": {"actions": [{"action": "<name>", "params": {...}}, ...]}}. Runs reads in parallel; individual failures are reported per-entry without short-circuiting. • context — {"action": "context", "params": {"topic": "<name>"}} or {"action": "context", "params": {"action": "<name>"}}. Returns deeper docs for a topic or a single action's signature. Plural "topics" / "actions" arrays are also accepted and may be combined. Topics: python, javascript, formula, connection, validation, a1, quadratic, chart, pivot_table. Action Reference • get_cell_data(selection, page?, sheet_name?) — Returns cell values for a selection in A1 notation. Supports comma-separated ranges to fetch multiple areas in ONE call, including across different sheets. Examples: "A1:B10, D1:E10", "TableName, OtherTable", "'Sheet1'!A1:B10, 'Sheet2'!C1:D10". Table names are globally unique so they work without sheet prefixes. For cell ranges on other sheets use 'SheetName'!Range. Only use when you need the full dataset (aggregations, lookups, analysis). The file summary already includes sample rows. Results may be paginated — use page (0-based) for additional pages. • has_cell_data(selection, sheet_name?) — Check if any cells in a selection have data. Returns true if ANY cell contains data. Use before creating/moving tables or code to avoid spill errors. All ranges MUST be on the same sheet. • get_code_cell_value(code_cell_position?, code_cell_name?, sheet_name?) — Get full code from an existing Python, JavaScript, or connection code cell. Do NOT use for formula cells — formulas are already in get_cell_data results and the file summary. • get_text_formats(selection, page?, sheet_name?) — Get text formatting info. Use table column references for tables ("Table_Name[Column Name]"). Results may be paginated. • get_validations(sheet_name?) — Get all validations in a sheet. • get_conditional_formats(sheet_name) — Get all conditional formatting rules. Use to check existing rules before creating/updating/deleting. • text_search(query, case_sensitive?, whole_cell?, search_code?, regex?, sheet_name?) — Search for text in cell outputs. Supports regex when enabled (e.g., "\d+", "^hello", "foo|bar"). Searches cell outputs only, not code. Booleans default false. • get_sheet_info() — List all sheets and names. • get_spreadsheet_context(sheet_name?, include_errors?) — Full context snapshot of the file. • read_data(selection, sheet_name?, max_rows?) — Read cell data as compact CSV. Auto-tiers: returns all rows for small/medium data (<5000 rows), head+tail preview for large data. Preferred over get_cell_data for most reads. • outline(sheet_name?) — Structural map of the file: sheets, bounds, tables, code cells, charts, connections, errors. Use to understand file layout before reading data. • dependencies(position, sheet_name?, direction?) — Trace cell dependencies. direction: "forward" (what this cell reads), "reverse" (what depends on this cell), or "both" (default). • export_pdf(options?) — Export the file as a PDF with Excel-parity print semantics. Returns {mime_type, size_bytes, data_base64}. options is a camelCase object: {sheetIds?: [id], fileName?, pageSetup?: {paperSize ("letter"|"legal"|"tabloid"|"a3"|"a4"|"a5"|...), orientation ("portrait"|"landscape"), margins {left,right,top,bottom,header,footer} (inches), scaling ({type:"zoom",percent} or {type:"fitTo",width?,height?}), pageOrder ("downThenOver"|"overThenDown"), centerHorizontally?, centerVertically?, printGridlines?, printHeadings?, header/footer {odd:{left,center,right}, even?, first?} with Excel codes (&P page, &N total, &D date, &T time, &F file, &A sheet, &B bold)}, sheetOptions?: {"<sheetId>": {pageSetup?, printArea? ("A1:F20"), repeatRows? ([1,2]), repeatCols?, rowBreaks?, colBreaks?}}}. Omit options for sensible defaults (letter portrait, 100% zoom, all sheets). • list_connections(team_uuid?) — List all database connections in a team (PostgreSQL, MySQL, MS SQL, Snowflake, BigQuery, Mixpanel, Google Analytics, Plaid, etc.). Returns each connection's uuid, name, and type. team_uuid is optional — if omitted, the user's only team is used; multi-team users must pass it. Call this BEFORE get_database_schemas or set_sql_code_cell_value to discover the connection_ids and connection types you need. • get_database_schemas(connection_ids, connection_type, team_uuid) — Get table/column schemas for database connections. Always call before writing SQL. Get connection_ids from list_connections. connection_type: POSTGRES, MYSQL, MSSQL, SNOWFLAKE, BIGQUERY, COCKROACHDB, etc. • list_agent_connections(team_uuid?) — List the team's ready Agent Connections (third-party REST API bindings). Returns each connection's uuid, name, service, base URL, auth pattern, and `{{SECRET_NAME}}` references to use in fetch code. team_uuid is optional — if omitted, the user's only team is used; multi-team users must pass it. Reference secrets via `{{SECRET_NAME}}` in Python/JavaScript fetch code; the connection proxy substitutes team secret values at request time. • inspect_agent_connection(connection_id, team_uuid?) — Get the full schema (resources, endpoints, fields, docs URLs) and plan for one ready Agent Connection by uuid (from list_agent_connections). Call BEFORE writing fetch code against a connection so you don't guess at endpoints. team_uuid is optional with the same single-team fallback as list_agent_connections. Batch: • batch(actions) — actions: [{action, params}]. Runs reads in parallel through this same tool; per-entry failures are reported in the result without short-circuiting the batch. `action` may be any name from this reference. Nested `context` items are allowed and returned alongside the reads.

  ConnectorNo auth

• create_userA

  mcpA

  Create a database user for a Cloud SQL instance. * This tool returns a long-running operation. Use the `get_operation` tool to poll its status until the operation completes. * When you use the `create_user` tool, specify the type of user: `CLOUD_IAM_USER`, `CLOUD_IAM_SERVICE_ACCOUNT`, or `BUILT_IN`. * By default the newly created user is assigned the `cloudsqlsuperuser` role, unless you specify other database roles explicitly in the request. * You can use a newly created user with the `execute_sql` tool if the user is a currently logged in IAM user. The `execute_sql` tool executes the SQL statements using the privileges of the database user logged in using IAM database authentication. The `create_user` tool has the following limitations: * To create a built-in user with password, use the `password_secret_version` field to provide password using the Google Cloud Secret Manager. The value of `password_secret_version` should be the resource name of the secret version, like `projects/12345/locations/us-central1/secrets/my-password-secret/versions/1` or `projects/12345/locations/us-central1/secrets/my-password-secret/versions/latest`. The caller needs to have `secretmanager.secretVersions.access` permission on the secret version. * The `create_user` tool doesn't support creating a user for SQL Server. To create an IAM user in PostgreSQL: * The database username must be the IAM user's email address and all lowercase. For example, to create user for PostgreSQL IAM user `example-user@example.com`, you can use the following request: ``` { "name": "example-user@example.com", "type": "CLOUD_IAM_USER", "instance":"test-instance", "project": "test-project" } ``` The created database username for the IAM user is `example-user@example.com`. To create an IAM service account in PostgreSQL: * The database username must be created without the `.gserviceaccount.com` suffix even though the full email address for the account is`service-account-name@project-id.iam.gserviceaccount.com`. For example, to create an IAM service account for PostgreSQL you can use the following request format: ``` { "name": "test@test-project.iam", "type": "CLOUD_IAM_SERVICE_ACCOUNT", "instance": "test-instance", "project": "test-project" } ``` The created database username for the IAM service account is `test@test-project.iam`. To create an IAM user or IAM service account in MySQL: * When Cloud SQL for MySQL stores a username, it truncates the @ and the domain name from the user or service account's email address. For example, `example-user@example.com` becomes `example-user`. * For this reason, you can't add two IAM users or service accounts with the same username but different domain names to the same Cloud SQL instance. * For example, to create user for the MySQL IAM user `example-user@example.com`, use the following request: ``` { "name": "example-user@example.com", "type": "CLOUD_IAM_USER", "instance": "test-instance", "project": "test-project" } ``` The created database username for the IAM user is `example-user`. * For example, to create the MySQL IAM service account `service-account-name@project-id.iam.gserviceaccount.com`, use the following request: ``` { "name": "service-account-name@project-id.iam.gserviceaccount.com", "type": "CLOUD_IAM_SERVICE_ACCOUNT", "instance": "test-instance", "project": "test-project" } ``` The created database username for the IAM service account is `service-account-name`.

  ConnectorNo auth

• get_webmasterA

  SpytrendA

  Fetch a single webmaster (affiliate NETWORK) by UUID: aggregate stats PLUS top_creatives — the creatives this webmaster re-uploads the MOST, ordered by the webmaster's OWN in-slice ad count (slice.ads_in_slice desc — the deliberate slice order, matching what the profile page shows), media stripped/free. Each entry's total_ads is the creative's market-wide family size, folded best-effort from family redirects and floored at ads_in_slice — total_ads == ads_in_slice therefore often means 'family cards not yet built', not 'this webmaster owns the whole market'; it is context, not the sort key. analytics_pending=true means the canonical PostgreSQL identity exists but its ClickHouse aggregate is not published yet, so zero counters are not analytical zeroes. fanpages_status explicitly reports advertiser-aligned lifecycle enrichment as available, partial, unavailable or not_applicable; an omitted fanpages array is therefore never evidence that a page is alive. The id MUST be the canonical UUID returned by search_webmasters; domain names and display names are rejected instead of silently widening to the whole database. Present top_creatives as the headline final step; for the rest of the network use search_creatives?webmaster_id / search_ads?webmaster_id, and download media with get_media (entity_type=creo). identifier_inventory_semantics explains why historical page/domain/pixel inventory counts are not comparable to total_ads. attribution_link_stats.merge_edges answers WHY these identifiers sit in one network: each entry is a {page_id, page_name, domain, ads} pair — that fanpage ran exactly that many ads on that landing domain, and such a pair is what merges two networks into one (an ad whose domain belongs to network A and whose fanpage belongs to network B fuses them permanently). Weigh the edges before claiming a single operator: a 1-3 ad edge next to 100+ ad edges is a thin bridge, typically a catalog/feed ad, and is weak evidence of shared ownership; identifiers with no edge at all are inherited from earlier merges and prove nothing today. QUOTA: 1 MCP credit (one entity card). TIKTOK: with source=tiktok this fetches the TikTok cluster card instead (business-id rollup, same UUID space as search_webmasters source=tiktok results) — ⚠️ costs 10 MCP credits and requires a Pro-or-higher plan; the Meta-only embeds (top_creatives, attribution link-stats) are omitted on the TikTok card. PRICING: on paid plans ×1 after 500 MCP credits/month; one-time consent via accept_pricing_terms; before calling, get the maximum debit from estimate_cost (free) and tell the user.

  ConnectorOAuth

• query_sqlA

  kad.devA

  Run ONE read-only SQL statement against the project's managed PostgreSQL database and return its rows — the same path as the dashboard DB console's read mode. Accepts a single statement starting with SELECT, WITH, EXPLAIN, SHOW, TABLE or VALUES; any ';' other than a trailing one is refused, even inside a string literal. Runs inside a PostgreSQL READ ONLY transaction, so a statement that tries to write fails in the database. Limits: 500 rows (truncated=true past that) and a 5-second statement timeout. Uses the project's own tenant credentials. Use execute_sql for INSERT, UPDATE, DELETE or schema changes.

  ConnectorOAuth

• open_er_diagramA

  ErdDocsA

  Open an interactive ER diagram of a database schema on erddocs.com. Use it when the user wants to see, understand, review or document their database structure, or asks for an ER diagram. Pass the schema text exactly as it is in the project. It reads SQL dumps and DDL (PostgreSQL, MySQL, SQL Server, SQLite), Prisma schema.prisma, DBML, Mermaid erDiagram, PlantUML, Django models.py, SQLAlchemy models, Sequelize models, TypeORM entities and a folder of Laravel migrations (concatenate the files). For SQL, the structure is enough: no INSERT data. Returns a link. The user opens it in a browser and gets the diagram with every table and relation laid out, relations without declared foreign keys found by column name and drawn dashed, and a data dictionary. Nothing is stored on the server: the schema travels inside the link and is parsed in the user's browser. A link holds a schema of a few dozen tables (about 100–200 characters of link per table, depending on comments); for a larger one the tool says so and the user pastes it on erddocs.com instead.

  ConnectorNo auth

• sixta_analyze_workloadA

  sixta-connectA

  Find your worst queries by TOTAL time — no connection needed. Paste a MySQL slow query log or a PostgreSQL pg_stat_statements export and get a ranked top-N: each query shape with calls, total/mean time, and (slow log) the rows-examined-to-sent ratio, fingerprinted so thousands of log lines collapse into a few classes. Flags the dominant query, N+1 patterns, and full-scan ratios, reports how concentrated the load is (what share of total time the top shapes own), and hands the worst offenders to sixta_analyze_query. Call this whenever the user shares a slow query log or pg_stat_statements export — even a long one — or asks which queries are slowest: summing time across thousands of log lines is arithmetic a model cannot do reliably by eye. Input is analyzed in memory and never stored.

  ConnectorOAuth

• create_databaseA

  mcpB

  Provisions a managed PostgreSQL database on a dedicated VM on your private network. Requires a recent plan_managed_datastore. For app deployments, prefer deploy_app database:'managed' so plan_deploy includes and wires the DB automatically. It is PRIVATE - reachable only from another instance on the same private network, via the DB's internal/private IP (not a public address). Get the ids from plan_managed_datastore/list_flavors/list_private_networks/list_keypairs. Provisioning takes ~5 min; poll list_databases until status='ready', then the connection details (private_ip, port 5432, db_name, db_user) are populated. HIGH AVAILABILITY: pass ha:true to get THREE machines on three different physical hosts behind a load balancer with automatic failover instead of one machine: the database survives losing a machine, and nobody has to fail it over by hand. It costs about 3x the hourly rate (three machines instead of one), it provisions more slowly, and one connection string still serves the whole thing. Default is a single machine; show the user the price difference and get an explicit yes before turning HA on.

  ConnectorNo auth

• zaira_compare_toolsA

  Zaira Labs GuideA

  Compare 2-3 developer tools, libraries or programming languages side by side. Returns each entry's full Markdown-KV block separated by "===". Alternatives and worksWith are enriched with tagline + agent-readiness for resolved slugs. If any requested slugs are not found, they appear in a trailing "Note: slugs not found: ..." line; the comparison still returns for the ones found. Examples: - Three search engines: {slugs: ["meilisearch-oss", "algolia", "elasticsearch-oss"]} - Two ORMs: {slugs: ["drizzle-orm", "prisma"]} - Three auth providers: {slugs: ["auth0", "clerk", "keycloak"]} - Hosted vs self-hosted for the same vendor: {slugs: ["redis-cloud", "redis-oss"]} — shows deployment trade-off - Postgres engine vs hosted offerings: {slugs: ["postgresql", "supabase-cloud", "cockroachdb-cloud"]} - Two languages for a CLI: {slugs: ["go", "rust"]} Edge cases: - Cross-category comparisons (e.g., {slugs: ["auth0", "redis-cloud"]}) are allowed but rarely useful. Same-category comparisons answer "which should I pick?" better; cross-category answers "these coexist in my stack" — a compatibility question. - Minimum 2 slugs, maximum 3. Four or more is a validation error; for more, run pairs. - Invalid or unknown slugs are listed under "slugs not found"; the partial comparison returns for valid ones. - Duplicate slugs in the array are deduplicated. - A few tools are single entries (no -cloud/-oss split): stripe, auth0, firebase, twilio, openai, pinecone, algolia. Don't pass "stripe-cloud" — it doesn't exist. Risk: read-only, closed-world, idempotent — no state change possible.

  ConnectorNo auth

• set-envA

  mcpA

  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.

  Connector

  Destructive

  No auth

• eol_statusA

  VigíaA

  Tells whether a language, runtime, framework, database or operating-system version is still supported and when it reaches end of life. Covers about 480 products (Python, Node.js, PHP, Java, Ruby, Go, Rust, Django, Laravel, Rails, React, Angular, PostgreSQL, MySQL, Ubuntu, Debian, Kubernetes and more). With product and version it returns that version's status (supported / security_only / end_of_life / upcoming), its release, active-support and end-of-life dates, days remaining or elapsed, and the cycles that are still supported; with only product it returns every release cycle; with neither it lists the product identifiers. Read-only and requires no authentication. Status is computed on every call from today's date; the dates come from endoflife.date and are refreshed every 12 hours. Use it before choosing a runtime or base image, when writing a Dockerfile or CI matrix, or when auditing an old version. It concerns the language, runtime or platform itself; for a library's own versions use package_status.

  ConnectorNo auth

• export_query_resultsA

  SaturnSQLA

  Run SQL on one connection and return the whole result as a file body in CSV, JSON or XLSX. Use it when the user wants a file to download, attach or load into another tool, or needs more rows than execute_query returns (10000 at most). To read or analyse rows yourself, use execute_query instead: it is smaller and returns structured rows. For a recurring export to Google Sheets or Slack, use create_schedule. On PostgreSQL and MySQL, omitting limit exports every row the query returns, bounded only by the query timeout; other engines stop at 100000 rows. Always reads the database, never the result cache. Read-only: only a single SELECT, WITH or EXPLAIN statement is accepted. Counts against the company's monthly query quota and a limit of 30 queries per minute. Needs the execute scope and a member role that can edit. CSV and JSON come back as text; XLSX comes back base64-encoded.

  ConnectorAPI key

• billing_budgetsA

  GreatWaitB

  Replaces the caller organization's advisory execution budget and optional hard execution-spend cap for the current UTC month. Values are exact whole cents encoded as integer microdollars. The expected budget-policy revision prevents a stale editor overwriting a newer choice, and Idempotency-Key makes retrying one intent safe. Null turns that setting off. This command records desired state durably; billing.reconcile advances it to PostgreSQL, and reads remain pending until PostgreSQL confirms it. It never changes automatic top-up authority, purchases credit, or counts subscription payments as execution usage.

  ConnectorOAuth

• revise_application_setupA

  AnkraB

  Negotiate the setup Ankra proposed for an Application by changing the defaults on its deploy option contract, and commit the rewritten .ankra/ankra.yaml to the Application's setup pull-request branch. Use this for requests like '8Gi is too much, this is a demo' (database_storage), 'make it highly available' (database_instances, replicas) or 'expose it at shop.example.com' (ingress_enabled, ingress_host). Call get_application_setup_proposal first: only options the contract already declares can be changed, and every value must satisfy that option's declared type. The revision is all-or-nothing - if any requested change is refused, the proposal is left exactly as it was and the answer names each refusal and why, so never re-offer the unchanged plan as though the request had been honoured. The database ENGINE is not an option: Ankra generates PostgreSQL through the CloudNativePG operator, and swapping it means regenerating the setup rather than revising its contract. This never deploys anything - it writes one commit on the setup branch and updates the stored contract; the user still has to deploy.

  ConnectorOAuth

• superdb_run_sqlA

  SuperDBA

  Executa SQL do PostgreSQL 16 (https://www.postgresql.org/docs/16/sql-commands.html) no schema do projeto SuperDB, podendo ALTERAR o banco: INSERT, UPDATE, DELETE e DDL (CREATE TABLE, ALTER, CREATE POLICY) — é o mesmo executor das migrations. Para consultas que só leem existe superdb_query_sql. SELECT sem LIMIT recebe LIMIT 1000 automaticamente; quando corta, a resposta traz "truncado": true e "limite_de_linhas": 1000 e a primeira linha avisa. Para ler mais, pagine com LIMIT/OFFSET ou keyset (WHERE id > último ORDER BY id LIMIT 1000).

  Connector

  Destructive

  OAuth

• sixta_analyze_schema_changeA

  sixta-connectA

  Call this whenever the user proposes a migration / DDL change or asks 'is this safe to run' — before answering from memory. Whether a migration locks the table is version-specific (exactly which MySQL 8.0.x or PostgreSQL version makes an ALTER lock-free, INSTANT vs INPLACE vs COPY eligibility), and model recall of those version boundaries is unreliable — this is where answering from memory most often ships an outage. Returns an explicit safety verdict per statement (Critical/High/Medium/Info), the exact lock taken and what it blocks, the MySQL algorithm verdict with version-specific eligibility, PostgreSQL rewrite triggers, replication and MDL-starvation warnings, and the safe execution strategy (CREATE INDEX CONCURRENTLY, NOT VALID + VALIDATE, gh-ost / pt-osc) as ready-to-run SQL. Optional table size/FK/trigger hints sharpen duration estimates; for entitled Connect Pro orgs these are filled from live production context automatically (an explicit argument still wins). Findings are deterministic, treat them as ground truth. Input is analyzed in memory and never stored.

  ConnectorOAuth

• sixta_explain_deadlockA

  sixta-connectA

  Reconstruct a database deadlock from the raw dump — no connection needed. Paste the LATEST DETECTED DEADLOCK section of MySQL's SHOW ENGINE INNODB STATUS, or a PostgreSQL 'deadlock detected' log entry, and get: which transaction held and waited for which lock, the inconsistent lock-ordering that caused the cycle, which transaction was rolled back, and the consistent-ordering / short-transaction / retry fix. Use when the user pastes a deadlock dump or asks 'why did this deadlock'. Input is analyzed in memory and never stored.

  ConnectorOAuth

• convoopenA

  InsideOut (Riley)A

  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.

  ConnectorNo auth

• convoopenA

  InsideOut (Riley)A

  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.

  ConnectorNo auth

• create_instanceA

  mcpA

  Initiates the creation of a Cloud SQL instance. * The tool returns a long-running operation. Use the `get_operation` tool to poll its status until the operation completes. * The instance creation operation can take several minutes. Use a command line tool to pause for 30 seconds before rechecking the status. * For MySQL and PostgreSQL instances, after you use the `create_instance` tool to create an instance, you can use the `create_user` tool to create an IAM user account for the user currently logged in to the project. * IMPORTANT: Set `ipv4_enabled` to 'false' if creating a Private Service Connect or a Private Service Access instance. * Set `free_trial` to 'true' to create a free trial instance. Free trial instances let you test majority of Cloud SQL features for up to 30 days without financial commitment. Subject to eligibility and availability. * The value of `data_api_access` is set to `ALLOW_DATA_API` by default. This setting lets you execute SQL statements using the `execute_sql` tool and the `executeSql` API. Unless otherwise specified, a newly created instance uses the default instance configuration of a development environment. The following is the default configuration for an instance in a development environment: ``` { "tier": "db-perf-optimized-N-2", "data_disk_size_gb": 100, "region": "us-central1", "database_version": "POSTGRES_18", "edition": "ENTERPRISE_PLUS", "availability_type": "ZONAL", "tags": [{"environment": "dev"}] } ``` The following configuration is recommended for an instance in a production environment: ``` { "tier": "db-perf-optimized-N-8", "data_disk_size_gb": 250, "region": "us-central1", "database_version": "POSTGRES_18", "edition": "ENTERPRISE_PLUS", "availability_type": "REGIONAL", "tags": [{"environment": "prod"}] } ``` The following instance configuration is recommended for SQL Server: ``` { "tier": "db-perf-optimized-N-8", "data_disk_size_gb": 250, "region": "us-central1", "database_version": "SQLSERVER_2022_STANDARD", "edition": "ENTERPRISE", "availability_type": "REGIONAL", "tags": [{"environment": "prod"}] } ```

  ConnectorNo auth