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MariaDB MCP Server

Official MariaDB MCP server for schema inspection, read-only SQL, optional database creation, and vector-store search against MariaDB databases.

by MariaDB · submitted by oktofeesh1·added 2026-06-06·
Review first review before installing

Open the source and read safety notes before installing.

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Source URLs
https://github.com/MariaDB/mcp#readme, https://github.com/MariaDB/mcp
Brand
MariaDB
Brand domain
mariadb.org
Brand asset source
brandfetch
Safety notes
MariaDB MCP connects Claude to a live database and exposes schema inspection plus SQL execution tools., The default read-only mode allows SELECT, SHOW, DESCRIBE, DESC, and USE-style queries, but the README warns that database privileges are the only reliable way to guarantee read-only access., The server includes a `create_database` tool and optional vector-store tools that can create, insert into, search, and delete vector-store tables when enabled., If `MCP_READ_ONLY=false` or credentials have broad privileges, model-generated SQL can create, modify, delete, or expose database state., The server checks for risky FILE privilege behavior, but teams should revoke FILE and other unnecessary global privileges from the connected MariaDB user., HTTP and SSE transports require explicit authentication and restricted host/origin settings before any non-local use., Embedding providers can receive document text or derived content when vector-store tooling is enabled.
Privacy notes
Database credentials, hostnames, database names, schemas, table names, column names, SQL text, query results, errors, and log files may be visible to the MCP client and model provider., MariaDB data can include customer records, credentials, audit logs, business metrics, payment data, healthcare data, or other regulated information., Vector-store tables can persist source documents, embeddings, metadata, and semantic-search results inside MariaDB., OPENAI_API_KEY, GEMINI_API_KEY, HF_MODEL settings, SSL certificate paths, dotenv files, and database passwords should stay out of prompts, issues, logs, screenshots, and committed files., Review log retention because the server writes logs to `logs/mcp_server.log` by default.
Author
MariaDB
Submitted by
oktofeesh1
Claim status
unclaimed
Last verified
2026-06-06

Decision playbook

Review trust signals before you adopt

Signals are present but mixed. Use the checklist below to confirm the source and operational safety for your environment.

Compare context
Selected

0

Current score

63

Baseline

Delta

No baseline selected

No major trust-signal divergence detected in the current selection.

Source and provenance checks

Needs review

Confirm ownership and provenance before trusting install instructions.

  • Source link availableRequired

    Open the canonical repository and verify ownership.

    Done
  • Source provenance statusRequired

    Marked as source-backed.

    Done
  • Metadata reviewed

    No reviewed flag detected in metadata.

    Pending

Safety and privacy checks

Complete

Validate risk disclosures before installation or API wiring.

  • Safety notes presentRequired

    Review the listed safety guidance before running commands.

    Done
  • Privacy notes presentRequired

    Review data handling notes before connecting accounts or secrets.

    Done
  • Trust level risk gateRequired

    Trust level does not block evaluation.

    Done

Package and install checks

Needs review

Check package metadata and artifact integrity signals.

  • Install payload available

    Install or copy payload is available for review.

    Done
  • Package verification flag

    No package verification flag provided.

    Pending
  • Checksum metadata

    No checksum provided for downloaded artifact.

    Pending

Compare-driven decision checks

Needs review

Use compare context to validate trade-offs before adoption.

  • Compare tray has multiple entries

    Add at least one more entry to compare trust differences.

    Pending
  • Baseline comparison available

    No baseline peer selected yet.

    Pending
  • Diverging trust signals identified

    No major trust-signal divergence found.

    Pending

Setup at a glance

CLI install

Copy-ready — paste the snippet to get started.

20 minutes

Adoption plan

Balanced adoption plan

Current risk score 24/100. Use staged verification before broader rollout.

Risk 24

Pre-adoption checks

Validate source and review signals before any execution.

  • Confirm source provenanceRequired

    Source URL/provenance metadata is present.

    Done
  • Confirm metadata review state

    No review metadata found; increase manual validation.

    Pending
  • Verify install payload

    Install/config payload exists and can be inspected.

    Done

Security checks

Confirm safety, privacy, and package integrity signals.

  • Review safety notesRequired

    Safety notes are present.

    Done
  • Review privacy notesRequired

    Privacy notes are present.

    Done
  • Verify package integrity metadata

    No package verification/checksum metadata.

    Pending

Rollout

Adopt in controlled steps based on the selected plan.

  • Run in isolated sandbox firstRequired

    Use a constrained sandbox and observe behavior across multiple tasks.

    Pending
  • Roll out graduallyRequired

    Roll out to a small cohort before wider usage.

    Pending
  • Set monitoring and fallback

    Define rollback path and monitor errors after adoption.

    Pending

Evidence readiness

Evidence readiness matrix · balanced

Missing required evidence: Metadata review. Risk score 31.

Risk 31

Source provenance

Present

Source repository/provenance is listed.

Required in this preset

Metadata review

Missing

Review metadata is missing.

Required in this preset

Safety notes

Present

Safety notes are present.

Required in this preset

Privacy notes

Present

Privacy notes are present.

Optional in this preset

Package integrity

Missing

Package integrity metadata is missing.

Optional in this preset

Install payload

Present

Install payload is available.

Required in this preset

Required gaps: Metadata review

Decision timeline

Decision timeline · balanced

Blocking gaps: Check metadata review status. Risk 28.

Risk 28

triage

Confirm source provenanceRequired

Source/provenance metadata is available.

Done

triage

Check metadata review statusRequired

Review metadata is missing.

Pending

verify

Review safety notesRequired

Safety notes are available.

Done

verify

Review privacy notes

Privacy notes are available.

Done

verify

Validate package integrity metadata

Package integrity metadata is missing.

Pending

rollout

Verify install payload and commandsRequired

Install payload is available.

Done

Blockers: Check metadata review status

Prerequisite readiness

Prerequisite readiness

6 prerequisites to line up before setup. Includes a review or approval gate.

0/6 ready
Install & runtime1Configuration1Permissions & scopes1Network & hosting1Review & approval220 minutes

Safety & privacy surface

Safety & privacy surface

7 safety and 5 privacy notes across 6 risk areas. Review closely: credentials & tokens, network access, third-party handling.

6 areas
  • SafetyGeneralMariaDB MCP connects Claude to a live database and exposes schema inspection plus SQL execution tools.
  • SafetyGeneralThe default read-only mode allows SELECT, SHOW, DESCRIBE, DESC, and USE-style queries, but the README warns that database privileges are the only reliable way to guarantee read-only access.
  • SafetyData retentionThe server includes a `create_database` tool and optional vector-store tools that can create, insert into, search, and delete vector-store tables when enabled.
  • SafetyCredentials & tokensIf `MCP_READ_ONLY=false` or credentials have broad privileges, model-generated SQL can create, modify, delete, or expose database state.
  • SafetyLocal filesThe server checks for risky FILE privilege behavior, but teams should revoke FILE and other unnecessary global privileges from the connected MariaDB user.
  • SafetyNetwork accessHTTP and SSE transports require explicit authentication and restricted host/origin settings before any non-local use.
  • SafetyThird-party handlingEmbedding providers can receive document text or derived content when vector-store tooling is enabled.
  • PrivacyCredentials & tokensDatabase credentials, hostnames, database names, schemas, table names, column names, SQL text, query results, errors, and log files may be visible to the MCP client and model provider.
  • PrivacyCredentials & tokensMariaDB data can include customer records, credentials, audit logs, business metrics, payment data, healthcare data, or other regulated information.
  • PrivacyData retentionVector-store tables can persist source documents, embeddings, metadata, and semantic-search results inside MariaDB.
  • PrivacyCredentials & tokensOPENAI_API_KEY, GEMINI_API_KEY, HF_MODEL settings, SSL certificate paths, dotenv files, and database passwords should stay out of prompts, issues, logs, screenshots, and committed files.
  • PrivacyData retentionReview log retention because the server writes logs to `logs/mcp_server.log` by default.

Safety notes

  • MariaDB MCP connects Claude to a live database and exposes schema inspection plus SQL execution tools.
  • The default read-only mode allows SELECT, SHOW, DESCRIBE, DESC, and USE-style queries, but the README warns that database privileges are the only reliable way to guarantee read-only access.
  • The server includes a `create_database` tool and optional vector-store tools that can create, insert into, search, and delete vector-store tables when enabled.
  • If `MCP_READ_ONLY=false` or credentials have broad privileges, model-generated SQL can create, modify, delete, or expose database state.
  • The server checks for risky FILE privilege behavior, but teams should revoke FILE and other unnecessary global privileges from the connected MariaDB user.
  • HTTP and SSE transports require explicit authentication and restricted host/origin settings before any non-local use.
  • Embedding providers can receive document text or derived content when vector-store tooling is enabled.

Privacy notes

  • Database credentials, hostnames, database names, schemas, table names, column names, SQL text, query results, errors, and log files may be visible to the MCP client and model provider.
  • MariaDB data can include customer records, credentials, audit logs, business metrics, payment data, healthcare data, or other regulated information.
  • Vector-store tables can persist source documents, embeddings, metadata, and semantic-search results inside MariaDB.
  • OPENAI_API_KEY, GEMINI_API_KEY, HF_MODEL settings, SSL certificate paths, dotenv files, and database passwords should stay out of prompts, issues, logs, screenshots, and committed files.
  • Review log retention because the server writes logs to `logs/mcp_server.log` by default.

Prerequisites

  • Python 3.11 and uv available to the MCP client runtime.
  • Reviewed checkout of the MariaDB MCP repository with dependencies installed.
  • MariaDB database host, port, database name, username, and password.
  • Least-privilege MariaDB user scoped to only the databases and operations Claude should access.
  • Keep `MCP_READ_ONLY=true` for exploration workflows unless a human explicitly approves write-capable tools.
  • Optional OpenAI, Gemini, or HuggingFace embedding configuration only when vector-store tools are needed.

Schema details

Install type
cli
Troubleshooting
No
Source repository stats
Scope
Source repo
Collection metadata
Estimated setup
20 minutes
Difficulty
advanced
Full copyable content
{
  "mcpServers": {
    "mariadb": {
      "command": "uv",
      "args": [
        "--directory",
        "<mariadb-mcp-checkout>",
        "run",
        "server.py"
      ],
      "env": {
        "DB_HOST": "<mariadb-host>",
        "DB_PORT": "3306",
        "DB_USER": "<least-privilege-user>",
        "DB_PASSWORD": "<mariadb-password>",
        "DB_NAME": "<approved-database>",
        "MCP_READ_ONLY": "true"
      }
    }
  }
}

About this resource

Content

MariaDB MCP Server is the official MariaDB Model Context Protocol server for connecting Claude and other MCP clients to MariaDB databases. It exposes tools for listing databases and tables, inspecting schemas, running read-only SQL, and optionally managing embedding-backed vector stores inside MariaDB.

The server is implemented with FastMCP and asyncmy. It runs from a Python checkout with uv, supports stdio by default, and can also run over SSE or streamable HTTP when operators configure authentication and network controls.

Source Review

These sources were reviewed on 2026-06-06. Prefer the live repository, README, package metadata, server implementation, configuration module, and license for current installation steps, environment variables, tool behavior, transport options, and safety notes.

Features

  • Official MariaDB MCP repository under MariaDB/mcp.
  • Python 3.11 server managed with uv.
  • Stdio transport by default, with optional SSE and streamable HTTP modes.
  • Database listing and table listing tools.
  • Schema inspection with column metadata and foreign-key relationships.
  • execute_sql tool for read-only SQL workflows when MCP_READ_ONLY=true.
  • create_database tool for database creation workflows.
  • Optional vector-store tools when an embedding provider is configured.
  • OpenAI, Gemini, and HuggingFace embedding provider support.
  • SSL/TLS environment variables for MariaDB connections.
  • Host, origin, log, pool-size, and read-only environment configuration.

Installation

Clone the MariaDB MCP repository, install dependencies with uv, create a reviewed .env, and configure the MCP client to launch the server from that checkout:

{
  "mcpServers": {
    "mariadb": {
      "command": "uv",
      "args": [
        "--directory",
        "<mariadb-mcp-checkout>",
        "run",
        "server.py"
      ],
      "env": {
        "DB_HOST": "<mariadb-host>",
        "DB_PORT": "3306",
        "DB_USER": "<least-privilege-user>",
        "DB_PASSWORD": "<mariadb-password>",
        "DB_NAME": "<approved-database>",
        "MCP_READ_ONLY": "true"
      }
    }
  }
}

Keep MCP_READ_ONLY=true for exploration, and enforce least privilege at the MariaDB user level before connecting important data.

Use Cases

  • Ask Claude to list accessible databases before choosing a target.
  • Inspect table schemas and foreign-key relationships before writing SQL.
  • Run reviewed SELECT queries against development or analytics databases.
  • Compare schema shape across MariaDB environments.
  • Prototype vector search over approved MariaDB tables.
  • Use OpenAI, Gemini, or HuggingFace embeddings for semantic search when that data flow is approved.
  • Keep database creation and vector-store mutation workflows behind human review.

Safety and Privacy

MariaDB MCP is a database control surface. Treat every query as executable code, use dedicated least-privilege credentials, and rely on database permissions rather than client-side filters alone. Keep read-only mode enabled by default, review generated SQL before execution, revoke global FILE privileges, and avoid connecting production or regulated datasets unless the MCP client, model session, and operators are approved for that access.

Vector-store features can persist documents, embeddings, and metadata in MariaDB, while external embedding providers may receive document text or derived content. Review provider terms, retention, logging, and data residency before turning those tools on.

Disclosure

MariaDB offers open-source and commercial database products and services. This listing is not sponsored, paid, or affiliate-driven, and it is scoped to the source-backed open repository for the MariaDB MCP server.

Duplicate Check

Existing content includes DBHub, a multi-database MCP server that can connect to MariaDB among other engines. This entry is distinct because it covers MariaDB/mcp, the official MariaDB-specific MCP server. No dedicated MariaDB MCP Server, MariaDB/mcp, or matching source URL entry was found in content/mcp.

Source citations

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How it compares

MariaDB MCP Server side by side with 3 alternatives on trust, install, platform support, and disclosed safety notes — all from reviewed registry metadata.

1 trust signal differ across this comparison (Submitter).

Field

Official MariaDB MCP server for schema inspection, read-only SQL, optional database creation, and vector-store search against MariaDB databases.

Open dossier

MCP server from Zilliz for connecting Claude to Milvus vector database collections, text search, vector search, hybrid search, inserts, deletes, indexes, collection loading, database switching, and collection metadata.

Open dossier

Official Pinecone Developer MCP server that connects Claude and other MCP clients to Pinecone projects and documentation for index management, record upserts, semantic search, cascading multi-index search, reranking, and documentation lookup over integrated-inference indexes.

Open dossier

Connect Claude to a Weaviate vector database — run hybrid search, inspect collection config, list tenants, and upsert objects — using Weaviate's built-in Model Context Protocol server.

Open dossier
Next steps
Trust
Review statusNot reviewedNot reviewedNot reviewedNot reviewed
Package trustPackage not verifiedPackage not verifiedPackage not verifiedPackage not verified
Source provenanceSource-backedSource-backedSource-backedSource-backed
SubmitterDiffersoktofeesh1oktofeesh1JSONbored
Install riskReview firstReview firstReview firstReview first
Notes Safety ✓ Privacy ✓ Safety ✓ Privacy ✓ Safety ✓ Privacy ✓ Safety ✓ Privacy ✓
BrandMariaDB logoMariaDBMilvus logoMilvusPinecone logoPinecone
Categorymcpmcpmcpmcp
SourceSource-backedSource-backedSource-backedSource-backed
AuthorMariaDBZillizPineconeWeaviate
Added2026-06-062026-06-062026-06-112026-06-17
Platforms
Harness
Source repo
Safety notesMariaDB MCP connects Claude to a live database and exposes schema inspection plus SQL execution tools. The default read-only mode allows SELECT, SHOW, DESCRIBE, DESC, and USE-style queries, but the README warns that database privileges are the only reliable way to guarantee read-only access. The server includes a `create_database` tool and optional vector-store tools that can create, insert into, search, and delete vector-store tables when enabled. If `MCP_READ_ONLY=false` or credentials have broad privileges, model-generated SQL can create, modify, delete, or expose database state. The server checks for risky FILE privilege behavior, but teams should revoke FILE and other unnecessary global privileges from the connected MariaDB user. HTTP and SSE transports require explicit authentication and restricted host/origin settings before any non-local use. Embedding providers can receive document text or derived content when vector-store tooling is enabled.Milvus MCP can read collection metadata, query collections, and run text, vector, text-similarity, multi-vector, and hybrid searches. Write-capable tools can create collections, insert data, upsert data, delete entities, create indexes, bulk insert records, load collections, release collections, and switch databases. The README notes that the environment file has higher priority than command-line arguments, so stale or unexpected environment settings can silently change the target Milvus instance. SSE and Streamable HTTP modes can expose database operations over HTTP and should be network-restricted. Remote Milvus or Zilliz Cloud credentials should be scoped to the collections and databases Claude is allowed to access.The server can create indexes and upsert records, so an agent with a write-capable API key can change live Pinecone project state. Run the npm package `@pinecone-database/mcp` through `npx`, which downloads and executes the published package on each launch; pin to a trusted version if reproducibility matters. Scope the Pinecone API key to the intended project and use read-only or least-privilege keys when index creation and writes are not needed. Require human review before `create-index-for-model` and `upsert-records` runs that mutate production indexes.The MCP server runs inside your Weaviate instance and respects its existing RBAC; scope the API key to least privilege. The object-upsert tool writes data — restrict write access to the collections Claude should modify.
Privacy notesDatabase credentials, hostnames, database names, schemas, table names, column names, SQL text, query results, errors, and log files may be visible to the MCP client and model provider. MariaDB data can include customer records, credentials, audit logs, business metrics, payment data, healthcare data, or other regulated information. Vector-store tables can persist source documents, embeddings, metadata, and semantic-search results inside MariaDB. OPENAI_API_KEY, GEMINI_API_KEY, HF_MODEL settings, SSL certificate paths, dotenv files, and database passwords should stay out of prompts, issues, logs, screenshots, and committed files. Review log retention because the server writes logs to `logs/mcp_server.log` by default.Milvus collections can contain embeddings, sparse vectors, scalar fields, IDs, document chunks, metadata, image or multimodal references, query logs, and retrieval results that reveal sensitive project or user data. Milvus URI, tokens, database names, collection names, vector payloads, filter expressions, and retrieved records should stay out of prompts, issues, logs, screenshots, and committed files. Search results can include private source content that may be re-exposed in model transcripts or downstream tickets. HTTP transports, debug tools, query traces, failed-search artifacts, backups, and benchmark datasets need retention and access-control review.The `PINECONE_API_KEY` is read from the MCP client environment and grants access to the associated Pinecone project; keep it out of prompts, notes, and committed files. Index names, configurations, namespaces, statistics, record contents, and search queries can be exposed to the MCP client and model provider. Records and search text may contain embedded documents, customer data, or proprietary content, so review what is sent into indexes and returned by searches. Documentation search and tool calls reach Pinecone endpoints such as api.pinecone.io, so network access and request metadata leave the local machine.Query text, retrieved objects, and collection metadata enter the MCP client context and the model's prompt. The Weaviate endpoint URL and API key are secrets — keep them in the client config or environment, not in shared repositories.
Prerequisites
  • Python 3.11 and uv available to the MCP client runtime.
  • Reviewed checkout of the MariaDB MCP repository with dependencies installed.
  • MariaDB database host, port, database name, username, and password.
  • Least-privilege MariaDB user scoped to only the databases and operations Claude should access.
  • Python 3.10 or newer.
  • uv installed for the README's recommended run path.
  • Running local or remote Milvus instance.
  • Milvus URI, token, and database name selected for the target environment.
  • Node.js 18 or newer with `npx` available.
  • Pinecone account and API key generated from the Pinecone console at app.pinecone.io.
  • MCP client that supports stdio server configuration, such as Claude Desktop or Cursor.
  • Awareness that index management and record tools require integrated-inference indexes.
  • A Weaviate instance on v1.37.1 or later (self-hosted or Weaviate Cloud).
  • The MCP server enabled on that instance via MCP_SERVER_ENABLED=true.
  • A Weaviate API key with the RBAC permissions for the collections Claude should reach.
  • An MCP client such as Claude Code or Claude Desktop.
Install
uv run server.py
git clone https://github.com/zilliztech/mcp-server-milvus.git && cd mcp-server-milvus && uv run src/mcp_server_milvus/server.py --milvus-uri <milvus-uri>
npx -y @pinecone-database/mcp
claude mcp add --transport http weaviate https://<your-weaviate-host>/v1/mcp
Config
{
  "mcpServers": {
    "mariadb": {
      "command": "uv",
      "args": ["--directory", "<mariadb-mcp-checkout>", "run", "server.py"],
      "env": {
        "DB_HOST": "<mariadb-host>",
        "DB_PORT": "3306",
        "DB_USER": "<least-privilege-user>",
        "DB_PASSWORD": "<mariadb-password>",
        "DB_NAME": "<approved-database>",
        "MCP_READ_ONLY": "true"
      }
    }
  }
}
{
  "mcpServers": {
    "milvus": {
      "command": "uv",
      "args": [
        "--directory",
        "mcp-server-milvus",
        "run",
        "src/mcp_server_milvus/server.py",
        "--milvus-uri",
        "<milvus-uri>"
      ]
    }
  }
}
{
  "mcpServers": {
    "pinecone": {
      "command": "npx",
      "args": ["-y", "@pinecone-database/mcp"],
      "env": {
        "PINECONE_API_KEY": "{pinecone-api-key}"
      }
    }
  }
}
{
  "mcpServers": {
    "weaviate": {
      "url": "https://<your-weaviate-host>/v1/mcp",
      "type": "http"
    }
  }
}
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