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Liquid logo
Health: ActiveRecent health check succeeded.Last checked 9/9/2026, 11:47:54 AM

Liquid

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View Repository2 GitHub StarsTotal stargazers on GitHub for the source repository (2 stars).Visit Website
api-integrationmcpdatabasesdata-extraction

Discovers APIs and databases, maps fields to typed records, and exposes deterministic fetch, query, write, and sense operations.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
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We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag โ€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON โ–พ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "ertad-family-liquid": {
      "command": "uvx",
      "args": [
        "liquid-mcp"
      ]
    }
  }
}

๐Ÿ’ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives๐Ÿ”— More in Aggregators

Overview

The ertad-family/liquid MCP server connects agents to HTTP APIs, databases, messaging systems, industrial protocols, and other agent interfaces through a common MCP entry point. It discovers an upstream interface, maps returned fields to a requested model, and handles concerns such as authentication, pagination, and normalization. An LLM may be used during discovery of undocumented REST APIs and field mapping, while runtime data operations do not call a model. Reach for it when you need to connect to changing or heterogeneous systems without writing and maintaining a separate connector for each one.

Use cases

โ€ขConnect an agent to an undocumented REST API without writing a custom connector
โ€ขFetch normalized records from multiple database types
โ€ขSearch or aggregate upstream data before sending it to a model
โ€ขReceive live events from email, MQTT, or supported device systems
โ€ขRepair an adapter after an upstream schema changes

Key features

โ€ขDiscovers APIs and database interfaces
โ€ขMaps responses to typed records
โ€ขSupports fetch, query, write, and sense operations
โ€ขHandles pagination and output normalization
โ€ขProvides server-side search and aggregation
โ€ขReturns structured recovery information

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Liquid.

Extracted Tool Capabilities
Discovers APIs and database interfaces
Maps responses to typed records
Supports fetch, query, write, and sense operations
Handles pagination and output normalization
Provides server-side search and aggregation
Returns structured recovery information

How Liquid works

What ertad-family/liquid MCP server does

The ertad-family/liquid MCP server provides a common interface for reaching different kinds of systems through four core operations: fetch, query, write, and sense. It can work with REST and GraphQL APIs, SOAP/WSDL, gRPC, WebSocket, SSE/NDJSON, MQTT, email systems, databases, other MCP or A2A agents, and several industrial or device protocols described by the project.

The server accepts an endpoint such as an HTTPS URL, a database DSN, a gRPC target, or another MCP server. It discovers the available interface and returns typed records shaped around the fields requested by the caller. Supported database examples include PostgreSQL, MySQL/MariaDB, SQLite, DuckDB, SQL Server, Neo4j, MongoDB, and Redis.

How it works

Discovery happens when an adapter is created. Interfaces with machine-readable descriptions, including OpenAPI, GraphQL, gRPC reflection, MCP, A2A, and WSDL, can be discovered without an LLM. Databases are introspected directly. An LLM backend is needed for undocumented REST APIs and field mapping; the README identifies LiteLLM as the route to OpenAI, Gemini, Anthropic, local models, and other providers.

After setup, the runtime transport is deterministic and does not make model calls for each operation. Liquid can flatten common pagination envelopes, normalize identifiers and timestamps, and normalize certain cross-source values such as monetary fields. It also supports server-side search, aggregation, text search, token limits, and verbosity controls. Errors can include a structured recovery action, such as retrying after rate limiting or repairing an adapter after an upstream change.

Setup and configuration

Install the package with pip install liquid-api. The bundled MCP command can be started with uvx --from 'liquid-api[mcp]' liquid-mcp. The project documents Python 3.12 or newer. Add the discovery extra when the server must use an LLM to discover undocumented REST APIs or map fields. Optional extras are documented for Gemini, gRPC, WebSocket, PostgreSQL, MySQL/MariaDB, Neo4j, and DuckDB.

The upstream connection is supplied as a URL, DSN, or protocol target. Credentials are handled as part of the upstream connection process, but the provided material does not define a single required environment variable or authentication configuration for the MCP command.

Tools and capabilities

The ertad-family/liquid MCP server exposes capabilities corresponding to these operations and supporting functions:

  • Fetch typed records from an adapter.
  • Query, search, aggregate, or text-search upstream data.
  • Write data when write access is explicitly enabled.
  • Sense live events from streams, mailboxes, MQTT, devices, or supported systems.
  • Estimate expected output size before fetching.
  • Normalize fields across sources and repair adapters after schema drift.
  • Create tool metadata describing cost, latency, caching, idempotency, and side effects.

The project also describes canonical intents for some actions and ambient tools for checking quota or listing adapters. Exact availability can depend on the selected transport and installed extras.

Read the full README โ†’View source on GitHub โ†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks โ€” not a rating.

GitHub stars
2
Stargazers on the source repository.
Last commit
3mo ago
Most recent push to the default branch.
Directory activity
4 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about Liquid

Run `uvx --from 'liquid-api[mcp]' liquid-mcp`, or install the package with `pip install liquid-api` to get the bundled MCP command.

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Technical Specs & Signals

Category๐Ÿ”—Aggregators
PricingFree
More technical detailsExpand โ–พ
TransportSTDIO
RuntimePython
AuthAPI key
LicenseAGPL-3.0
ClientsClaude Desktop, Cursor, Windsurf, Cline / VS Code
Last updatedSep 5, 2026
Views4
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars2
GitHub Star CountTotal stargazers on GitHub representing community popularity (2 stars).
Last commit3mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Jun 9, 2026
51Quality signal: Good ยท 51/100How this signal is calculated โ–พ
Server availabilityNot measured

Not scored for repo-hosted servers โ€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools25/30
Adoption & activity2/15
Community engagement1/10

A guidance signal from public completeness & health data โ€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 17d ago via OSV.dev ยท liquid-mcp (PyPI)

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AllMCPs Server

The official MCP server for AllMCPs.com - submit and manage tools directly from your AI. The open directory for MCP servers. Connect Claude, Cursor, Windsurf, and AI agents to databases, tools, files, and APIs. Explore 10,000+ servers. AllMCPs is the premier, open directory for discovering, evaluating, and installing Model Context Protocol (MCP) servers to equip AI agents and LLMs with real-world superpowers.

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More in ๐Ÿ”— Aggregators โ†’Alternatives to Liquid โ†’Install in Claude DesktopInstall in CursorInstall in VS Code