Vector Search — In-Memory TF-IDF Semantic Store

axel-belfort/vector-search

•last deployed

99.48% uptime

In-memory vector search API for AI agents. Store documents and query by semantic meaning using TF-IDF vectorization with cosine similarity...

Performance

Usage

Integrate

Integrate this server via the CLI, MCP SDK, or AI SDK. Smithery handles OAuth, token refresh, and session management for you.

Create API key Manage Connections

1. Install Smithery CLI

2. Create a namespace

3. Use this server

# Add this server
smithery mcp add axel-belfort/vector-search

# List available tools
smithery tool list {connection}

# Call a tool
smithery tool call {connection} {tool_name} '{"key": "value"}'

Overview

Performance

Usage

Integrate

Vector Search — In-Memory TF-IDF Semantic Store

axel-belfort/vector-search

•last deployed

76/100

99.48% uptime

In-memory vector search API for AI agents. Store documents and query by semantic meaning using TF-IDF vectorization with cosine similarity...

Performance

Tool

Calls

No tool calls recorded.

Total

0

Uptime (30d)99.5%

Latency (30d)772ms p50

Performance

Usage

Top Clients

1

Smithery2

Total3

Daily Sessions

Usage

Integrate

Integrate this server via the CLI, MCP SDK, or AI SDK. Smithery handles OAuth, token refresh, and session management for you.

Create API key Manage Connections

1. Install Smithery CLI

2. Create a namespace

3. Use this server

# Add this server
smithery mcp add axel-belfort/vector-search

# List available tools
smithery tool list {connection}

# Call a tool
smithery tool call {connection} {tool_name} '{"key": "value"}'

76/100

Performance

Tool

Calls

No tool calls recorded.

Total

0

Uptime (30d)99.5%

Latency (30d)772ms p50

Usage

Top Clients

1

Smithery2

Total3