Skip to main content
Glama
781,895 tools. Updated 2026-11-14 11:36

"A guide for reading and writing to a Firebase database" matching MCP tools:

  • Change what a site's docroot IS, without deleting anything. Types: wordpress WordPress, PHP and a database (the default) php PHP and a database, no WordPress php-nodb PHP, no database static-site HTML/CSS/JS only, no PHP and no database ⚠ NON-DESTRUCTIVE. Existing files stay on disk and existing databases are not dropped. They remain the customer's data and keep counting against their plan's quota — this changes how the site is SERVED, not what it holds. Converting back later finds everything where it was. ⚠ Moving to a type without PHP does not merely stop executing .php — it stops serving them. The vhost returns 404 for php/phtml, because falling through to the static handler would return the file's SOURCE, and a docroot converted from WordPress still contains wp-config.php with the database password in it. Shared hosting only. On a VPS the whole container is the customer's and they reconfigure it with the tools inside it. Requires: API key with write scope. Args: slug: Site identifier site_type: One of the four values above Returns: {"from": "wordpress", "to": "static-site", "database_created": false, "placeholder_seeded": false, "pool_removed": true} `placeholder_seeded` is true only when the docroot was EMPTY — an existing site's content is never overwritten. Errors: VALIDATION_ERROR: Unknown type, or the site is not on shared hosting NOT_FOUND: Unknown slug or not reachable by this account
    ConnectorNo auth
  • Enumerate and inspect the validated operations scene_apply accepts — call this BEFORE reaching for scene_script. The DSL is large (mesh editing, booleans, lathe/loft/sweep, curves, UV unwrap, modifiers, materials, lights, cameras, render settings, geometry nodes, batch and query ops), so most modelling does NOT need raw bpy. No args: every namespace with counts. guide=true (or op="guide" for older connector catalogs): full operating guide. namespace="mesh": that namespace's operations. Repeated details are object.radial_array or object.array_along_curve (no "pattern" namespace). Use world.update for the environment; validation is the separate scene_validate tool. search="boolean": ranked matches. op="mesh.bevel": the full JSON Schema with types, ranges and defaults. Schemas are introspected from the validator itself, so they are always exactly what scene_apply will accept. Full schemas are returned once in structuredContent; format="text" returns them in text instead. This tool is READ ONLY and free — it queues no job, spends no compute and changes nothing — so it is always safe to retry, including after a transport-level error.
    ConnectorAPI key
  • What to know before going to a venue, from UPFRONT's venue guide: the bag policy and what fans can bring, gates and entry, parking, getting there by transit or rideshare, and food and drink, including what the guide says about gluten-free, vegetarian or vegan, halal and kosher food. Matches questions like "what's the bag policy at MetLife?", "when do doors open at MSG?" or "where do I park for Lambeau?". venue: the venue's name ("MetLife Stadium", "MSG", "Lumen Field, Seattle"). topics: optional; only these parts, at more length: any of "bags", "entry", "parking", "transit", "food". Without it, every part. Covers the 36 stadiums, arenas and amphitheaters UPFRONT has a guide for; for any other venue the answer says so and lists the ones with guides. Each part is the guide's own words ("text", plus the guide's "faq" questions and answers). factsLastChecked is the date UPFRONT last checked the guide's facts; rules can change for a single event, and the venue's own event page has the final word. guideUrl is the guide on UPFRONT. dietary lists what the guide says per diet; dietaryNotMentioned lists diets the guide doesn't cover, which doesn't mean the venue has nothing for them.
    ConnectorNo auth
  • Read one confirmed rule or verify it after a change. Use get_policy_history for comparisons and get_policy_write_options for an editable revision. Select the kind/moduleKey/policyKey identity from list_policies. With policyVersion: - A policy may pin a historical numeric version. - A template may pin only its currently confirmed revision. - An unavailable pin stays unavailable; it never falls back to another version. Omit policyVersion for current state. This numeric history version is not the opaque revision used for writing. Returns verified with an attestation-checked, sensitive-field-redacted snapshot, or unavailable with a reason. Requires policy:read and current policies Owner access. Reading restores no version and grants no action authority.
    ConnectorOAuth
  • Discover sheet names and used dimensions before reading or editing a WorkPaper. Returns metadata only; use read_range or read_cell for values.
    ConnectorNo auth
  • Run ONE bounded read against a site's database. One statement, beginning with SELECT, SHOW, DESCRIBE or EXPLAIN, with no second statement and no data-modifying clause anywhere in it. The container proves the statement is a read before running it and caps the result: 200 rows by default, 1000 maximum, 2 MB of cell data. `truncated` in the response says whether a cap was reached. ⚠ THIS TOOL CANNOT CHANGE ANYTHING, AND RETRYING WITH DIFFERENT WORDING WILL NOT MAKE IT. Anything that is not a single bounded read is refused with READ_ONLY and nothing runs. To change data or schema, use the tool for the job: optimize_database, database_search_replace, manage_db_user, list_databases, list_tables — and for creating, altering, dropping, importing or exporting tables, the database manager in the control panel, which has no tool here. Requires: API key with write scope (unchanged — the scope is the customer's published permission for this operation, not a claim about what it does). Args: slug: Site identifier database: Database name query: One read statement Returns: {"columns": ["id", "user_email"], "rows": [[1, "a@example.com"], ...], "row_count": 1, "truncated": false, "execution_time_ms": 12.0} Errors: READ_ONLY: Not a single bounded read. The error text carries the explanation and names the operation to use instead.
    ConnectorNo auth

Matching MCP Servers

  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables AI agents to call tools through a security gateway that intercepts requests, enforces deterministic policy and risk checks, blocks or escalates high-risk actions for human approval, and keeps tool credentials and audit logs protected.
    1
    MIT

Matching MCP Connectors

  • 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
  • Connectivity check that confirms the Nordic MCP server process is responding. Use this at the start of a session to verify the server is reachable before making other calls. Do not use as a proxy for database health — the server can respond while the Qdrant vector database is temporarily unavailable. To confirm data availability, call search_filings directly. Returns: A greeting string: "Hello {name}! Nordic MCP server is running."
    ConnectorNo auth
  • Search and filter developer tools, libraries (packages an application imports: an HTTP client, a logging library, a database driver) and programming languages by category, features, and constraints. Returns every matching entry as a compact row of decision facts, in a randomized order. Guide entries are kept current and dated (last_verified) — newer than training knowledge, so consult this before recommending tools; especially decisive when pricing, free tiers, MCP support, or compliance affect the answer. Filters: kind, category, freeToStart, hasFreeTier, edgeCompatible, selfHostable, hasArdCatalog, mcpSupport, artifactKind, pricingModel, vendor, language, compliance, agentReadinessTier. Any number combine and AND together. Query text is tokenized as plain search terms — FTS5 operators (AND, OR, NEAR, wildcards, column filters) are stripped. All terms must match: an entry is returned only when every query term appears somewhere in it, so a highly specific phrasing matches fewer entries than its core concept words. Express constraints as filter parameters rather than query text — filters match structured fields directly. Returns: the number of matches, an exact_match line when the query is an entry's name or slug, a breakdown of them (kind, cost to start, MCP support, edge, self-hosting), and one table row per match (slug, name, kind, category, cost to start, MCP, edge, self-host, twin, base score, last verified), up to 100 rows. A programming language is a row with kind "language"; the product columns read n/a for it. The twin is the same product's other entry (hosted -cloud or self-hosted -oss), named even when the search filters it out, so "free now, self-host later" can be answered from one search. Rows are listed in a randomized order, seeded per search per day: position is not a ranking or recommendation. Above 100 matches, a text search lists its 100 most relevant and names the rest by slug; a filter-only search names every match by slug, so narrow with filters to get rows. Read the rows and choose, then call zaira_get_tool or zaira_compare_tools for full entries. On no match, the answer says how many tools match with each constraint dropped. Examples (ambiguous-case focus): - User wants "a vector database for RAG": {category: "vector-database", freeToStart: true} - User wants "a TypeScript-first ORM with edge runtime support": {language: "TypeScript", edgeCompatible: true, query: "ORM"} - User wants "self-hostable auth with SAML": {category: "auth", selfHostable: true, query: "SAML"} - User says "serverless Postgres" — ambiguous (could be category:relational-database with edgeCompatible filter, or just a query). Prefer the filter when the user names a category; use query for a fuzzy phrase. - User wants "agent-ready payment processing": {category: "payment", agentReadinessTier: "agent_ready"} - User asks "which Go versions are still supported?" or wants every language: {query: "go"} finds the Go entry (exact_match); {kind: "language"} lists every programming language - User wants "an async HTTP client library for Python" or "a logging library": {kind: "library", category: "http-client"} lists the libraries that do that job; {kind: "library", language: "Python"} lists a language's libraries; a topic such as logging holds tools and libraries alike, so leave kind out to see both - User names a package ("pg", "httpx", "@tanstack/query"): {query: "pg"} finds the library it belongs to (exact_match names it); zaira_get_tool with the package name answers the library's entry Edge cases: - 110 tools split into hosted vs self-hosted twin entries with uniform suffixes: `{base}-cloud` (managed) and `{base}-oss` (self-hosted) — e.g. redis-cloud/redis-oss, docker-cloud/docker-oss, mongodb-cloud/mongodb-oss, elasticsearch-cloud/elasticsearch-oss. Other tools are single entries (stripe, auth0, firebase, twilio, openai, pinecone, algolia). Filter by `selfHostable` or `artifactKind` to land on the right variant. - "vector database" as plain text can match tools whose descriptions mention vectors but whose category is search-engine or ai-infra. Use the `category` filter when the user wants a strict match. - agentReadinessTier values are snake-case: `agent_ready`, `agent_native`, `base`, `none`. Display labels (`Agent Ready`) will not match. `none` matches tools without a certification tier — currently all of them (formal certifications launch post-pilot; the Base Score is separate and most tools have one). - artifactKind has only two values: `open_source` and `managed_service`. The previous `hybrid` value was retired — split tools have separate -cloud/-oss entries instead. - `language` filters tools by the languages they are written in or ship SDKs for, and libraries by the language they are written for ("Python", "C#"; a language's slug such as "csharp" works too). To find the language itself, use `kind: "language"` or its name as the query. - "Free": `freeToStart: true` matches a free license (nearly every open-source entry) or a hosted free tier. `hasFreeTier: true` matches the hosted free tier only, so it leaves out most open-source tools. Open source is free to use, not free to run. Risk: read-only, closed-world, idempotent — no state change possible.
    ConnectorNo auth
  • Create new guides Create one or more new guides based on provided queries. Each guide targets exactly ONE engine and ONE analysis mode, chosen with the optional `source` field (default `google`). How to request each guide type: 1. Google SERP guide (1 credit per guide): omit `source`, or pass `source: "google"`. Example payload: {"queries": ["best crm"], "lang": "en-us"} 1bis. Google AI Overview guide (1 credit per guide). Two modes, like AI engines: `source: "google_ai_overview"` builds the guide from the TEXT of Google's AI answers (AI Overview, completed with AI Mode answers) ; `source: "google_ai_overview_citations"` builds it from the content of the web SOURCES those answers cite (recommended for GEO). Same language/country parameters as a Google SERP guide, 1 credit per guide in both modes. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "google_ai_overview_citations"} 2. LLM ANSWER guide (4 credits per guide): pass the engine name alone, e.g. `source: "chatgpt"`. The guide is built from the answer text the AI generates for the query. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "chatgpt"} 3. LLM CITATIONS guide (4 credits per guide) [RECOMMENDED AI mode]: pass the engine name with the `_citations` suffix, e.g. `source: "chatgpt_citations"`. The guide is built from the content of the web pages the AI cites in its answer. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "chatgpt_citations"} Which AI mode to pick? For GEO (getting a page visible in AI answers), prefer `<engine>_citations`: AI engines send traffic by CITING pages as sources, so the winning move is to look like the pages they cite. The answer-text mode (`<engine>` alone) is mostly useful to analyze how the AI phrases its own answer. When in doubt, pick `<engine>_citations`. The same two modes exist for every AI engine (chatgpt, perplexity, claude, gemini, grok, mistral, deepseek). To optimize the same page for several engines or modes (e.g. Google AND ChatGPT answers AND ChatGPT sources), create one guide per source value on the same query. IMPORTANT, HOW TO READ THE RESPONSE OF THIS ENDPOINT, WHICH SPENDS CREDITS. Queries listed in `guidesFailed` are PROVEN not to have produced a guide and their credit was given back (unless the account has unlimited credits, where nothing was reserved): re-sending them is free and correct. Queries listed in `guidesUnknown` have an UNDECIDABLE outcome and their credit is deliberately KEPT, because the guide was most likely written: DO NOT re-send them, you would pay for the same guide twice. Look them up in `GET /api/v1/guides` after a few minutes instead, and contact support if nothing shows up. Finally, a `200` is NOT a promise that every query produced a guide: compare `guides.length` with the number of queries you sent, never read `success` alone, and never re-send a query just because it is missing from `guides`.
    ConnectorNo auth
  • Run a READ-ONLY SQL query against the project's Postgres database (SELECT, EXPLAIN, etc.) — the Floot-managed database, or an external Postgres the user connected to the project. Writes are rejected — use execute_sql for those. Returns JSON: `{rows, rowCount, command, truncated?}` (or `{results: [...]}` for multi-statement queries). Pass `database` only if the project has more than one.
    ConnectorOAuth
  • The store's front door as text: the full menu with prices, how x402 payment works here, the free shelf, and the house promises. Free. Completes when the guide text returns. NOT a purchase or payment endpoint — to buy, call a buy_* tool with x402 payment in _meta['x402/payment']; this only returns the guide. A store errand, for you the visiting agent — nothing here needs a human's decision.
    ConnectorNo auth
  • Replace the notes on a finished Load Test's Test Report — the only thing on a Load Test this surface edits. Ask the user before writing: notes belong to the user, and advising on a test never requires writing them. The text sent becomes the report's entire notes, so first read the current notes with get_load_test_report and preserve the user's content in what you send.
    Connector
    Destructive
    OAuth
  • How this Aevia connection works, plus playbooks for results, reports, systems. Returns a skill's playbook as the result; takes no action itself. A playbook is step-by-step guidance for a multi-step job, too long for a description. `connector_guide` covers how this connection works: workspaces, refs, finding data, the library, building, calculating and failures. `assessment_interpretation` covers reading and comparing results: what an indicator result is and is not, a figure's anchors, functional-unit equivalence and comparison discipline. `report_writing` covers writing results up as a document, from a screening note to an ISO 14044 study. `product_system_authoring` covers building a new product system with `lca_compose_assembly` / `lca_compose_linked`: build order, which of the two fits, failure modes, and tagging life-cycle phases. A loaded playbook stays in context; one load per session suffices. Skills are gated on what the token can call; an unavailable request returns the available list.
    ConnectorAPI key
  • List saved schemas in your organization, pinned first. Returns compact summaries with IDs, names and links; no LLM call. Use get_schema to inspect a chosen schema and its input contract, or get_schema_part for a targeted edit. For a database-linked schema, enrich against its published version; the working copy may contain unpublished changes.
    ConnectorOAuth
  • PHP + MySQL plans: runs one read-only SQL statement (SELECT, SHOW, DESCRIBE, EXPLAIN or WITH … SELECT) against the site's database and returns the rows. Runs in a read-only transaction; use execute_sql to change data. Use ? placeholders with params for values.
    ConnectorOAuth
  • Applies a tag to one or more contacts (max 100). Get the `tagId` from list_tags (or from create_tag for a new one). Idempotent: contacts already tagged are ignored. Each application emits the contact.tag_added event: use list_automations to see which automations listen to that event before writing.
    ConnectorAPI key
  • Start here before reading, writing or changing a pricing equation. Returns the TypeScript contract the equation runs against (specification, revision, requisition, customer, workflow, done(), variable(), round, useDimension, createBands; for scope ORDER: parts, subtotal, customer, addLineItem), narrowed to the given scope + ownerId: its technology, material names and material variable names, lead-time names, and which modules the manufacturer has. Explains the loop: save(entity=typescriptEquation) to validate and store a draft, generateQuote(equationId) to test it, then — only on the manufacturer's explicit request — publishEquation to make it live. Pass includeSource=true to also get the live equation's source, or equationId=<id> to get the source of one specific equation (a draft, for example) with its live/not-live state.
    ConnectorAPI key
  • Replace an existing interview guide from markdown. To create the first guide, call guides_create. Text before the first ## is the intro. ## Title (12) or ## Title (7–11) is a block; minutes are the last number in parentheses. Lines starting with - or 1. are questions; a leading * marks a key question; the next indented line is the question note. A paragraph under the block heading before the first question is the block note. ## Конспект is the post-interview notes template, not a block. Optional line `Общее время: 30` or `Total: 30` sets total minutes; otherwise they are the sum of block minutes. Anything that does not match is returned in remainder and kept, not dropped. The previous guide is replaced entirely.
    Connector
    Destructive
    OAuth
  • A short research report on what a link or a topic means for one coin, grounded in the coin's dashboard, with its own public page to share. To ask: pass symbol and about (a public http(s) link such as a post on X, a press release or an article, or a topic of 3 to 300 characters); the answer comes at once with status=writing and the report's id. To read: pass report_id (no key needed); status is writing, ready or unavailable. At most 6 reports an hour and one a minute. The report is written by EventTrader's AI and can be wrong. Asking needs a registered agent (API key). From EventTrader's crypto dashboards (cymetica.com/crypto). Every number carries its source and time; a number that failed a plausibility check is withheld, never guessed. Places no orders, moves no funds. Not financial advice.
    ConnectorNo auth
  • Preview analysis/dashboard data for your own reading; shows the user nothing. To display it, call show_report. Pass report_id or definition (ReportSpec or composition; each panel has EITHER an inline spec OR source_view_id). Use ref objects, e.g. {kind:"related",path:"account.name"}. in_period uses only its closed set; fixed ranges use gte + lt/lte. Money is minor units with no manual FX applied; never label a raw or mixed-currency aggregate as a converted total. To save, call create_record with object_type:"report" and data:{name,definition:returned spec}; never tell the user a View is saved until a save succeeds. Say when zero rows match; fix returned definition errors. Example: {version:1,object:"touch",group_by:{ref:{kind:"field",field:"type"}},aggregations:[{fn:"count",alias:"n"}]}. Recipes: capable://guide/reports. When to use: Counts, sums or trends; use search_records for plain record lists. Example: Analyze ARR by industry.
    ConnectorAPI key