Voice Bridge runs on your own machine — the client starts it, so there is no endpoint to ping. 107 installs a week from pypi. Last commit 29 Apr 2026.
Multi-engine TTS for AI coding assistants. 5 engines, free engine included.
We read the source, 19 h ago · rules 3dff92dd89df
Things with no honest explanation: a promise that contradicts the code, code that runs at install time while hiding what it does, data leaving the machine.
emit "Install failed. Install uv: curl -LsSf https://astral.sh/uv/install.sh | sh"
What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.
const out = execFileSync(whichCmd(), [name], {
subprocess.run(cmd, stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
Code changes quietly between releases, and nobody reads the diff of a dependency. We do, on every release — watch Voice Bridge and you get told the day something new turns up.
This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.
claude mcp add voice-bridge -- npx -y ai-voice-bridge
{
"mcpServers": {
"voice-bridge": {
"args": [
"-y",
"ai-voice-bridge"
],
"command": "npx"
}
}
}
[mcp_servers.voice-bridge]
command = "npx"
args = ["-y", "ai-voice-bridge"]
{
"mcpServers": {
"voice-bridge": {
"args": [
"-y",
"ai-voice-bridge"
],
"command": "npx"
}
}
}
{
"mcpServers": {
"voice-bridge": {
"args": [
"-y",
"ai-voice-bridge"
],
"command": "npx"
}
}
}
Natural voice conversations for AI assistants - STT/TTS via MCP
SQL analytics and data engineering for AI Assistants and IDEs
Team engineering memory for AI coding assistants. 47 MCP tools, pgvector semantic search.
Local codebase search for AI assistants via MCP. Requires Hawkeye and Hawkeye AI Bridge installed.
MCP server bridging AI assistants to OpenAI Codex CLI for code analysis and review
MCP server bridging OpenGrok search engine with AI for instant context across massive codebases.
Memory layer for AI coding assistants. Indexes git history + code, exposes via MCP.
MCP memory server for AI coding assistants. Windows Service, ONNX embeddings, SQLite vector search.
Answers built from our own checks of this server.