meilisearch
The python client for Meilisearch API.
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has low install friction, carries no known vulnerabilities, and is MIT-licensed. Install it if you are already running a Meilisearch server and need a straightforward Python client for indexing and search. Not suitable if you require async/await support (use the community fork instead) or if you do not have a Meilisearch instance to connect to.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires a running Meilisearch server instance (self-hosted or Meilisearch Cloud) and Python 3.10 or higher.
- Low install friction with only two runtime dependencies (requests and camel-converter).
- Active maintenance with a recent release 23 days ago and consistent commit history.
License · maintenance · safety
MIT (permissive) — MIT license permits unrestricted use, modification, and distribution in both open-source and commercial projects with minimal obligations.
last release 2026-07-22 (23 days) · last repo commit 2026-08-01 · 600 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 938,281 downloads/mo, #4,686 on PyPI
Alternatives
Verify before relying
pip install meilisearch
import meilisearch
client = meilisearch.Client('http://127.0.0.1:7700', 'masterKey')
index = client.index('movies')
index.add_documents([{'id': 1, 'title': 'Carol'}])
results = index.search('carol')- Whether the package's async support story has changed since the description recommends a community fork (meilisearch-python-sdk) for async/await.
- Current feature parity with Meilisearch server versions beyond v1.2.
What it is and what it does
Meilisearch is a Python client that connects your application to a Meilisearch search engine instance. It abstracts the HTTP API into a straightforward object-oriented interface for indexing documents and running searches. The package handles document serialization, index management, and query construction, supporting both simple keyword searches and advanced features like typo tolerance, filtering, highlighting, and hybrid search (combining keyword and semantic search via embedders).
The client is synchronous and designed for standard request-response workflows. It depends on requests for HTTP communication and camel-converter for data transformation. The package is actively maintained, supports modern Python versions (3.10–3.13), and carries no known security vulnerabilities. If your project requires async/await, the description notes that a community-maintained fork exists, though this package itself remains synchronous.
Use it for
- Add full-text search to a web application by indexing product or content documents and serving typo-tolerant queries.
- Build a search interface with filtering and highlighting by configuring filterable attributes and custom search parameters.
- Combine keyword and semantic search in a single query using hybrid search with configured embedders for relevance ranking.
- Manage document lifecycle (add, update, delete) and track indexing tasks via the task API for large datasets.
- Serialize complex Python objects (UUIDs, datetimes) into searchable documents using a custom JSON encoder.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has low install friction, carries no known vulnerabilities, and is MIT-licensed. Install it if you are already running a Meilisearch server and need a straightforward Python client for indexing and search. Not suitable if you require async/await support (use the community fork instead) or if you do not have a Meilisearch instance to connect to.
Install
meilisearch on PyPI
Before you install
Low install friction with only two runtime dependencies (requests and camel-converter). Active maintenance with a recent release 23 days ago and consistent commit history. Supports Python 3.10+ across current language versions.
Requires a running Meilisearch server instance (self-hosted or Meilisearch Cloud) and Python 3.10 or higher.
License in practice
MIT license permits unrestricted use, modification, and distribution in both open-source and commercial projects with minimal obligations.
Quickstart
pip install meilisearch
import meilisearch
client = meilisearch.Client('http://127.0.0.1:7700', 'masterKey')
index = client.index('movies')
index.add_documents([{'id': 1, 'title': 'Carol'}])
results = index.search('carol')Verify before relying
- Whether the package's async support story has changed since the description recommends a community fork (meilisearch-python-sdk) for async/await.
- Current feature parity with Meilisearch server versions beyond v1.2.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesrequestscamel-converter |
| Maintenance | Actively maintained 23 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 938,281 / month, #4,686 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | License :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13 |
Evidence: meilisearch-0.43.0-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
An agent finds packages by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language. Give your agent the search over MCP.
More Front-Ends packages
SQLAlchemy is a Python SQL toolkit and Object Relational Mapper (ORM) that provides both a high-level ORM layer for declarative object persistence and a Core SQL construction system for direct database abstraction and query building.
psycopg2-binary is a PostgreSQL database adapter for Python that implements the DB API 2.0 specification, enabling Python applications to connect to and query PostgreSQL databases with thread-safe concurrent operations.
Alembic generates and manages database schema migrations for SQLAlchemy applications, handling version control of database structure changes with support for upgrades, downgrades, and auto-generation from model changes.
Install it if you use SQLAlchemy and need to version-control schema changes; skip it only if you manage migrations manually or use a different ORM entirely.
A Python client library for connecting to and querying Weaviate, a vector database that enables semantic search and AI-powered data retrieval.
A Python client library that connects to Databricks clusters and SQL warehouses using a Thrift-based protocol, conforming to the Python DB API 2.0 specification and supporting Arrow-based data exchange.
Install it if you need to query Databricks clusters or SQL warehouses from Python.
Psycopg 3 is a PostgreSQL database adapter for Python that enables applications to connect to, query, and manage PostgreSQL databases using Python code.
Install it if you need to connect Python to PostgreSQL.
See also meilisearch-python-sdk · redisvl · azure-search-documents · pagefind · pagefind-bin · metal-sdk · pinecone-text · Whoosh · llama-index-retrievers-bm25 · FlagEmbedding