Which embedding models does it support?

It integrates with OpenAI and Jina embedding models for semantic vector search.

Does it support typo tolerance in search?

Yes, it uses the naver/efficient-splade-VI-BT-large-query model for typo-tolerant neural sparse-vector search.

Can I use my own models?

Yes, you can bring your own text-embedding, SPLADE, cross-encoder re-ranking, or LLM models.

What filtering options are available?

Supports date-range, substring match, tag, numeric, and other filter types.

Trieve

searchvector-searchsemantic-searchretrieval-augmented-generationself-hosting

Self-hosted semantic and neural search server with chunking, vector search, typo tolerance, recommendations, and RAG support.

Quick Install

Automated & IDE Setup

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

Add to Cursor Add to VS Code

We couldn’t automatically confirm this listing starts correctly

We ran the install command below but it didn't respond within our test window — this can mean a slow first-time install rather than a real problem.

npx -y @smithery/cli

No response to initialize.

This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked 4d ago.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "devflowinc-trieve": {
      "command": "npx",
      "args": [
        "-y",
        "@smithery/cli"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Overview

This server enables crawling, embedding, chunking, and searching datasets using semantic dense vector and typo-tolerant neural sparse-vector search. It supports self-hosting in your VPC or on-premises with integrations for OpenAI, Jina embeddings, and Qdrant vector database. Features include sub-sentence highlighting, recommendations, hybrid search with re-ranking, recency biasing, filtering, grouping, and convenient RAG API routes with OpenRouter integration. It is suitable for applications needing advanced search, recommendation, and retrieval-augmented generation capabilities on custom dat…

Use cases

Implement semantic search over large document collections

Build typo-tolerant full-text and neural search interfaces

Provide content recommendations based on similarity

Enable retrieval-augmented generation with custom context

Self-host search infrastructure within private networks

Key features

Self-hosting support for AWS, GCP, Kubernetes, Docker Compose

Semantic dense vector search with OpenAI/Jina embeddings and Qdrant

Typo tolerant neural sparse-vector search using SPLADE model

Sub-sentence highlighting of matched query terms

Recommendation API for similar chunks or files

RAG API routes integrated with OpenRouter for LLM access

Capabilities & Tool Schemas

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

Extracted Tool Capabilities

Self-hosting support for AWS, GCP, Kubernetes, Docker Compose

Semantic dense vector search with OpenAI/Jina embeddings and Qdrant

Typo tolerant neural sparse-vector search using SPLADE model

Sub-sentence highlighting of matched query terms

Recommendation API for similar chunks or files

RAG API routes integrated with OpenRouter for LLM access

Documentation Overview

All-in-one solution for search, recommendations, and RAG

Quick Links

Features

🔒 Self-Hosting in your VPC or on-prem: We have full self-hosting guides for AWS, GCP, Kubernetes generally, and docker compose available on our documentation page here.
🧠 Semantic Dense Vector Search: Integrates with OpenAI or Jina embedding models and Qdrant to provide semantic vector search.
🔍 Typo Tolerant Full-Text/Neural Search: Every uploaded chunk is vector'ized with naver/efficient-splade-VI-BT-large-query for typo tolerant, quality neural sparse-vector search.
🖊️ Sub-Sentence Highlighting: Highlight the matching words or sentences within a chunk and bold them on search to enhance UX for your users. Shout out to the simsearch crate!
🌟 Recommendations: Find similar chunks (or files if using grouping) with the recommendation API. Very helpful if you have a platform where users' favorite, bookmark, or upvote content.
🤖 Convenient RAG API Routes: We integrate with OpenRouter to provide you with access to any LLM you would like for RAG. Try our routes for fully-managed RAG with topic-based memory management or select your own context RAG.
💼 Bring Your Own Models: If you'd like, you can bring your own text-embedding, SPLADE, cross-encoder re-ranking, and/or large-language model (LLM) and plug it into our infrastructure.
🔄 Hybrid Search with cross-encoder re-ranking: For the best results, use hybrid search with BAAI/bge-reranker-large re-rank optimization.
📆 Recency Biasing: Easily bias search results for what was most recent to prevent staleness
🛠️ Tunable Merchandizing: Adjust relevance using signals like clicks, add-to-carts, or citations
🕳️ Filtering: Date-range, substring match, tag, numeric, and other filter types are supported.
👥 Grouping: Mark multiple chunks as being part of the same file and search on the file-level such that the same top-level result never appears twice

Are we missing a feature that your use case would need? - call us at 628-222-4090, make a Github issue, or join the Matrix community and tell us! We are a small company who is still very hands-on and eager to build what you need; professional services are available.

Local Development

Installing via Smithery

To install Trieve for Claude Desktop automatically via Smithery:

Terminal

npx -y @smithery/cli install trieve-mcp-server --client claude

System Dependencies

Linux (Debian/Ubuntu)

sudo apt install curl \
gcc \
g++ \
make \
pkg-config \
python3 \
python3-pip \
libpq-dev \
libssl-dev \
openssl

Linux (Arch)

sudo pacman -S base-devel postgresql-libs

MacOS

# Install Xcode command line tools
xcode-select --install

# Install Homebrew if not already installed
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

# Install required packages
brew install pkg-config openssl

Install NodeJS and Yarn

You can install NVM using its install script.

Terminal

curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.5/install.sh | bash

You should restart the terminal to update bash profile with NVM. Then, you can install NodeJS LTS release and Yarn.

Code

nvm install --lts
npm install -g yarn

Make server tmp dir

Code

mkdir server/tmp

Install rust

Terminal

curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

Install cargo-watch

Code

cargo install cargo-watch

Setup env's

You might need to create the analytics directory in ./frontends

Code

cp .env.analytics ./frontends/analytics/.env
cp .env.chat ./frontends/chat/.env
cp .env.search ./frontends/search/.env
cp .env.example ./server/.env
cp .env.dashboard ./frontends/dashboard/.env

Add your `LLM_API_KEY` to `./server/.env`

Here is a guide for acquiring that.

Steps once you have the key

Open the ./server/.env file
Replace the value for LLM_API_KEY to be your own OpenAI API key.
Replace the value for OPENAI_API_KEY to be your own OpenAI API key.

Override the following keys in your terminal for local dev

The PAGEFIND_CDN_BASE_URL and S3_SECRET_KEY_CSVJSONL can be set to a random list of strings.

server.ts

export OPENAI_API_KEY="your_OpenAI_api_key" \
LLM_API_KEY="your_OpenAI_api_key" \
PAGEFIND_CDN_BASE_URL="lZP8X4h0Q5Sj2ZmV,aAmu1W92T6DbFUkJ,DZ5pMvz8P1kKNH0r,QAqwvKh8rI5sPmuW,YMwgsBz7jLfN0oX8" \
S3_SECRET_KEY_CSVJSONL="Gq6wzS3mjC5kL7i4KwexnL3gP8Z1a5Xv,V2c4ZnL0uHqBzFvR2NcN8Pb1g6CjmX9J,TfA1h8LgI5zYkH9A9p7NvWlL0sZzF9p8N,pKr81pLq5n6MkNzT1X09R7Qb0Vn5cFr0d,DzYwz82FQiW6T3u9A4z9h7HLOlJb7L2V1" \
GROQ_API_KEY="GROQ_API_KEY_if_applicable"

Start docker container services needed for local dev

Code

cat .env.chat .env.search .env.server .env.docker-compose > .env

./convenience.sh -l

Start embedding servers

We offer 2 docker-compose files for embedding servers. One for GPU and one for CPU.

Terminal

docker compose -f docker-compose-cpu-embeddings.yml up -d

Terminal

docker compose -f docker-compose-gpu-embeddings.yml up -d

Note on embedding servers. If you want to use a separate GPU enabled device for embedding servers you will need to update the following parameters

Code

SPARSE_SERVER_QUERY_ORIGIN
SPARSE_SERVER_DOC_ORIGIN
EMBEDDING_SERVER_ORIGIN
SPARSE_SERVER_QUERY_ORIGIN

Using CPU embeddings on MacOS

Code

cp docker-compose-cpu-embeddings.override.mac docker-compose-cpu-embeddings.override.yml
docker-compose -f docker-compose-cpu-embeddings.yml -f docker-compose-cpu-embeddings.override.yml docker up -d

Install front-end packages for local dev

Code

cd frontends
yarn

cd ..

Code

cd clients/ts-sdk
yarn build

cd ../..

Start services for local dev

It is recommend to manage services through tmuxp, see the guide here or terminal tabs.

Code

cd frontends
yarn
yarn dev

Code

cd server
cargo watch -x run

Code

cd server
cargo run --bin ingestion-worker

Code

cd server
cargo run --bin file-worker

Code

cd server
cargo run --bin delete-worker

Code

cd search
yarn
yarn dev

Verify Working Setup

After the cargo build has finished (after the tmuxp load trieve):

check that you can see redoc with the OpenAPI reference at localhost:8090/redoc
make an account create a dataset with test data at localhost:5173
search that dataset with test data at localhost:5174

Additional Instructions for testing cross encoder reranking models

Read the full README →View source on GitHub →

Related MCP Servers

View all in Search & Data Extraction View all alternatives

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

2.7k

Stargazers on the source repository.

npm downloads

30k

Package downloads in the last 30 days.

Last commit

7mo ago

Most recent push to the default branch.

Install check

Inconclusive

Didn't respond in our test window — often a slow first install.

Directory activity

2 views

Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Trieve

Yes, full self-hosting guides are available for AWS, GCP, Kubernetes, and Docker Compose.

AllMCPs Directory Badge

Full Badge Customizer

Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.

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Markdown (GitHub README)

[![AllMCPs](https://allmcps.com/api/badge/devflowinc-trieve?style=directory)](https://allmcps.com/mcp/devflowinc-trieve)

HTML Embed

<a href="https://allmcps.com/mcp/devflowinc-trieve"><img src="https://allmcps.com/api/badge/devflowinc-trieve?style=directory" alt="Trieve on AllMCPs" /></a>

Technical Specs & Signals

CategorySearch & Data Extraction

PricingFreemium

10/10 checks healthy over the last 32d

49Quality signal: Fair · 49/100How this signal is calculated ▾

Server availabilityNot measured

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

Verified ownership10/20

Documentation & tools17/30

Adoption & activity10/15

Community engagement0/10

A guidance signal from public completeness & health data — 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 23d ago via OSV.dev · @smithery/cli (npm)

★ Featured

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.

Explore Server →

Own this project?

This directory is pre-filled from public sources. Claim via GitHub README, site badge, or DNS TXT to unlock edit access and the Official badge — proof is checked automatically, then reviewed by our team.

Free dofollow backlink: add your website and place the AllMCPs badge on it — no claim needed. We detect it automatically and keep it verified as long as the badge stays live.

Claim & get free dofollow

Share & Embed

Add our SVG badge (dark/light directory styles) or embeddable widget to your site.

Explore more

More in 🔎 Search & Data Extraction →Best MCP servers for Web Search & Scraping →Alternatives to Trieve →Install in Claude Desktop Install in Cursor Install in VS Code

Trieve

searchvector-searchsemantic-searchretrieval-augmented-generationself-hosting

Self-hosted semantic and neural search server with chunking, vector search, typo tolerance, recommendations, and RAG support.

Quick Install

Automated & IDE Setup

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

Add to Cursor Add to VS Code

We couldn’t automatically confirm this listing starts correctly

We ran the install command below but it didn't respond within our test window — this can mean a slow first-time install rather than a real problem.

npx -y @smithery/cli

No response to initialize.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "devflowinc-trieve": {
      "command": "npx",
      "args": [
        "-y",
        "@smithery/cli"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Overview

Use cases

Implement semantic search over large document collections

Build typo-tolerant full-text and neural search interfaces

Provide content recommendations based on similarity

Enable retrieval-augmented generation with custom context

Self-host search infrastructure within private networks

Key features

Self-hosting support for AWS, GCP, Kubernetes, Docker Compose

Semantic dense vector search with OpenAI/Jina embeddings and Qdrant

Typo tolerant neural sparse-vector search using SPLADE model

Sub-sentence highlighting of matched query terms

Recommendation API for similar chunks or files

RAG API routes integrated with OpenRouter for LLM access

Capabilities & Tool Schemas

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

Extracted Tool Capabilities

Self-hosting support for AWS, GCP, Kubernetes, Docker Compose

Semantic dense vector search with OpenAI/Jina embeddings and Qdrant

Typo tolerant neural sparse-vector search using SPLADE model

Sub-sentence highlighting of matched query terms

Recommendation API for similar chunks or files

RAG API routes integrated with OpenRouter for LLM access

Documentation Overview

All-in-one solution for search, recommendations, and RAG

Quick Links

Features

🔒 Self-Hosting in your VPC or on-prem: We have full self-hosting guides for AWS, GCP, Kubernetes generally, and docker compose available on our documentation page here.
🧠 Semantic Dense Vector Search: Integrates with OpenAI or Jina embedding models and Qdrant to provide semantic vector search.
🔍 Typo Tolerant Full-Text/Neural Search: Every uploaded chunk is vector'ized with naver/efficient-splade-VI-BT-large-query for typo tolerant, quality neural sparse-vector search.
🖊️ Sub-Sentence Highlighting: Highlight the matching words or sentences within a chunk and bold them on search to enhance UX for your users. Shout out to the simsearch crate!
🌟 Recommendations: Find similar chunks (or files if using grouping) with the recommendation API. Very helpful if you have a platform where users' favorite, bookmark, or upvote content.
🤖 Convenient RAG API Routes: We integrate with OpenRouter to provide you with access to any LLM you would like for RAG. Try our routes for fully-managed RAG with topic-based memory management or select your own context RAG.
💼 Bring Your Own Models: If you'd like, you can bring your own text-embedding, SPLADE, cross-encoder re-ranking, and/or large-language model (LLM) and plug it into our infrastructure.
🔄 Hybrid Search with cross-encoder re-ranking: For the best results, use hybrid search with BAAI/bge-reranker-large re-rank optimization.
📆 Recency Biasing: Easily bias search results for what was most recent to prevent staleness
🛠️ Tunable Merchandizing: Adjust relevance using signals like clicks, add-to-carts, or citations
🕳️ Filtering: Date-range, substring match, tag, numeric, and other filter types are supported.
👥 Grouping: Mark multiple chunks as being part of the same file and search on the file-level such that the same top-level result never appears twice

Local Development

Installing via Smithery

To install Trieve for Claude Desktop automatically via Smithery:

Terminal

npx -y @smithery/cli install trieve-mcp-server --client claude

System Dependencies

Linux (Debian/Ubuntu)

sudo apt install curl \
gcc \
g++ \
make \
pkg-config \
python3 \
python3-pip \
libpq-dev \
libssl-dev \
openssl

Linux (Arch)

sudo pacman -S base-devel postgresql-libs

MacOS

# Install Xcode command line tools
xcode-select --install

# Install Homebrew if not already installed
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

# Install required packages
brew install pkg-config openssl

Install NodeJS and Yarn

You can install NVM using its install script.

Terminal

curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.5/install.sh | bash

You should restart the terminal to update bash profile with NVM. Then, you can install NodeJS LTS release and Yarn.

Code

nvm install --lts
npm install -g yarn

Make server tmp dir

Code

mkdir server/tmp

Install rust

Terminal

curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

Install cargo-watch

Code

cargo install cargo-watch

Setup env's

You might need to create the analytics directory in ./frontends

Code

cp .env.analytics ./frontends/analytics/.env
cp .env.chat ./frontends/chat/.env
cp .env.search ./frontends/search/.env
cp .env.example ./server/.env
cp .env.dashboard ./frontends/dashboard/.env

Add your `LLM_API_KEY` to `./server/.env`

Here is a guide for acquiring that.

Steps once you have the key

Open the ./server/.env file
Replace the value for LLM_API_KEY to be your own OpenAI API key.
Replace the value for OPENAI_API_KEY to be your own OpenAI API key.

Override the following keys in your terminal for local dev

The PAGEFIND_CDN_BASE_URL and S3_SECRET_KEY_CSVJSONL can be set to a random list of strings.

server.ts

export OPENAI_API_KEY="your_OpenAI_api_key" \
LLM_API_KEY="your_OpenAI_api_key" \
PAGEFIND_CDN_BASE_URL="lZP8X4h0Q5Sj2ZmV,aAmu1W92T6DbFUkJ,DZ5pMvz8P1kKNH0r,QAqwvKh8rI5sPmuW,YMwgsBz7jLfN0oX8" \
S3_SECRET_KEY_CSVJSONL="Gq6wzS3mjC5kL7i4KwexnL3gP8Z1a5Xv,V2c4ZnL0uHqBzFvR2NcN8Pb1g6CjmX9J,TfA1h8LgI5zYkH9A9p7NvWlL0sZzF9p8N,pKr81pLq5n6MkNzT1X09R7Qb0Vn5cFr0d,DzYwz82FQiW6T3u9A4z9h7HLOlJb7L2V1" \
GROQ_API_KEY="GROQ_API_KEY_if_applicable"

Start docker container services needed for local dev

Code

cat .env.chat .env.search .env.server .env.docker-compose > .env

./convenience.sh -l

Start embedding servers

We offer 2 docker-compose files for embedding servers. One for GPU and one for CPU.

Terminal

docker compose -f docker-compose-cpu-embeddings.yml up -d

Terminal

docker compose -f docker-compose-gpu-embeddings.yml up -d

Note on embedding servers. If you want to use a separate GPU enabled device for embedding servers you will need to update the following parameters

Code

SPARSE_SERVER_QUERY_ORIGIN
SPARSE_SERVER_DOC_ORIGIN
EMBEDDING_SERVER_ORIGIN
SPARSE_SERVER_QUERY_ORIGIN

Using CPU embeddings on MacOS

Code

cp docker-compose-cpu-embeddings.override.mac docker-compose-cpu-embeddings.override.yml
docker-compose -f docker-compose-cpu-embeddings.yml -f docker-compose-cpu-embeddings.override.yml docker up -d

Install front-end packages for local dev

Code

cd frontends
yarn

cd ..

Code

cd clients/ts-sdk
yarn build

cd ../..

Start services for local dev

It is recommend to manage services through tmuxp, see the guide here or terminal tabs.

Code

cd frontends
yarn
yarn dev

Code

cd server
cargo watch -x run

Code

cd server
cargo run --bin ingestion-worker

Code

cd server
cargo run --bin file-worker

Code

cd server
cargo run --bin delete-worker

Code

cd search
yarn
yarn dev

Verify Working Setup

After the cargo build has finished (after the tmuxp load trieve):

check that you can see redoc with the OpenAPI reference at localhost:8090/redoc
make an account create a dataset with test data at localhost:5173
search that dataset with test data at localhost:5174

Additional Instructions for testing cross encoder reranking models

Read the full README →View source on GitHub →

Related MCP Servers

View all in Search & Data Extraction View all alternatives

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

2.7k

Stargazers on the source repository.

npm downloads

30k

Package downloads in the last 30 days.

Last commit

7mo ago

Most recent push to the default branch.

Install check

Inconclusive

Didn't respond in our test window — often a slow first install.

Directory activity

2 views

Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Trieve

Yes, full self-hosting guides are available for AWS, GCP, Kubernetes, and Docker Compose.

AllMCPs Directory Badge

Full Badge Customizer

Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.

Badge Style:

Live Dynamic SVG Preview

Markdown (GitHub README)

[![AllMCPs](https://allmcps.com/api/badge/devflowinc-trieve?style=directory)](https://allmcps.com/mcp/devflowinc-trieve)

HTML Embed

<a href="https://allmcps.com/mcp/devflowinc-trieve"><img src="https://allmcps.com/api/badge/devflowinc-trieve?style=directory" alt="Trieve on AllMCPs" /></a>

Technical Specs & Signals

CategorySearch & Data Extraction

PricingFreemium

10/10 checks healthy over the last 32d

49Quality signal: Fair · 49/100How this signal is calculated ▾

Server availabilityNot measured

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

Verified ownership10/20

Documentation & tools17/30

Adoption & activity10/15

Community engagement0/10

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 23d ago via OSV.dev · @smithery/cli (npm)

★ Featured

AllMCPs Server

Explore Server →

Own this project?

Free dofollow backlink: add your website and place the AllMCPs badge on it — no claim needed. We detect it automatically and keep it verified as long as the badge stays live.

Claim & get free dofollow

Share & Embed

Add our SVG badge (dark/light directory styles) or embeddable widget to your site.

Explore more

More in 🔎 Search & Data Extraction →Best MCP servers for Web Search & Scraping →Alternatives to Trieve →Install in Claude Desktop Install in Cursor Install in VS Code

Trieve

Quick Install

Client Config & Setup

Overview

Use cases

Key features

Capabilities & Tool Schemas

Documentation Overview

All-in-one solution for search, recommendations, and RAG

Quick Links

Features

Local Development

Installing via Smithery

System Dependencies

Linux (Debian/Ubuntu)

Linux (Arch)

MacOS

Install NodeJS and Yarn

Make server tmp dir

Install rust

Install cargo-watch

Setup env's

Add your LLM_API_KEY to ./server/.env

Steps once you have the key

Override the following keys in your terminal for local dev

Start docker container services needed for local dev

Start embedding servers

Using CPU embeddings on MacOS

Install front-end packages for local dev

Start services for local dev

Verify Working Setup

Additional Instructions for testing cross encoder reranking models

Related MCP Servers

Adoption & maintenance

Reviews

Frequently Asked Questions about Trieve

AllMCPs Directory Badge

Technical Specs & Signals

Supply-chain signal

AllMCPs Server

Own this project?

Share & Embed

Explore more

Trieve

Quick Install

Client Config & Setup

Overview

Use cases

Key features

Capabilities & Tool Schemas

Documentation Overview

All-in-one solution for search, recommendations, and RAG

Quick Links

Features

Local Development

Installing via Smithery

System Dependencies

Linux (Debian/Ubuntu)

Linux (Arch)

MacOS

Install NodeJS and Yarn

Make server tmp dir

Install rust

Install cargo-watch

Setup env's

Add your LLM_API_KEY to ./server/.env

Steps once you have the key

Override the following keys in your terminal for local dev

Start docker container services needed for local dev

Start embedding servers

Using CPU embeddings on MacOS

Install front-end packages for local dev

Start services for local dev

Verify Working Setup

Additional Instructions for testing cross encoder reranking models

Related MCP Servers

Adoption & maintenance

Reviews

Frequently Asked Questions about Trieve

AllMCPs Directory Badge

Add your `LLM_API_KEY` to `./server/.env`

Add your `LLM_API_KEY` to `./server/.env`