Skip to main content
Glama

SautiMesh

Voice-first, offline-first multilingual and code-switching AI agent runtime for Africa and the global edge.

Version Python License: MIT DPG Aligned

SautiMesh (Sauti = Voice in Swahili + Mesh = resilient edge-first durability) empowers community health workers, smallholder cooperatives, emergency responders, mobile money agents, and global field developers to build offline-first voice agents across Swahili (sw), Luganda (lg), Yoruba (yo), Hausa (ha), French (fr), English (en), Nigerian Pidgin (pcm), and Runyankole (nyn) without burning mobile data or USD cloud budgets.


Why SautiMesh Exists (Research-Backed Design)

Mainstream agent frameworks (LangGraph, CrewAI, AutoGen) assume continuous broadband, English-only inputs, and cloud Postgres/API connectivity. Real-world field deployments show why that fails:

  1. Connectivity & Power Reality (GSMA & IEA): Roughly 63% of Africa lives within broadband coverage yet stays offline, and nearly 600M lack reliable power. Agents need ACID local persistence (SQLite WAL) and store-and-forward retry queues instead of split-brain cloud sessions.

  2. Code-Switching Speech Reality (Masakhane, Sunbird AI, Lelapa AI): Real speakers naturally mix languages mid-sentence ("Habari daktari, mtoto ana fever kali leo"). SautiMesh tags tokens per language, computes a Code-Switch Index (CSI), preserves tonal diacritics (ẹ, ọ, ṣ), and grounds idioms before reaching an LLM.

  3. Budget & Carrier Physics: USSD caps packets at 160 bytes (182 GSM-7 / 80 UCS-2 chars) and SMS splits at 160 GSM-7 / 70 UCS-2. SautiMesh formats every spoken agent reply with single-SMS fallback, USSD pagination summaries, local-currency (UGX, KES, NGN, GHS, XOF, ZAR, RWF, TZS, USD) hard spend caps, and local PII redaction before cloud calls.


Related MCP server: collab-charter

Core Architecture

 16kHz PCM / Voice Note ──▶ Pure-Python VAD & SNR Check (or Silero / whisper.cpp / MMS)
                                     │
                                     ▼
                     Code-Switch & Lexicon Guard
        (sw / lg / yo / ha / fr / en / pcm / nyn · PII Redact · GSM-7/UCS-2 Pack)
                                     │
         ┌───────────────────────────┼───────────────────────────┐
         ▼                           ▼                           ▼
   Stage 1: Offline Playbooks   Stage 2: Edge SLM          Stage 3: Gated Cloud
   (0 ms · 0 bytes · $0.00)     (Ollama / Sunflower v2)   (FX Cap + PII Stripped)
         └───────────────────────────┼───────────────────────────┘
                                     ▼
             SQLite WAL Store-and-Forward Queue + Spoken WAV & SMS Receipt

Quickstart

Zero external runtime dependencies required on Python 3.11+:

git clone https://github.com/codesphere-u/sautimesh.git
cd sautimesh
pip install -e .

# Analyze a mixed Swahili + English utterance with PII redaction
sautimesh analyze "Habari daktari, mtoto ana fever kali leo PIN: 4829"

# Execute a deterministic offline-first voice turn with SQLite persistence
sautimesh chat --text "Ssebo obuwuka bungi mu kasooli farm yange leero" --currency UGX

# Run the built-in 7-case multilingual & emergency-escalation benchmark suite
sautimesh eval

# Start the interactive Voice Workbench & Simulator at http://127.0.0.1:8765
sautimesh serve

# Export DPGA Open Source AI Transparency & Limitation Card
sautimesh dpg-card --format markdown

Pluggable Speech & Model Adapters

SautiMesh ships zero-bloat pure-Python fallbacks (OfflineAcousticFallbackASR, OfflineCadenceTTS) so tests, CI gates, and Termux Android phones run reliably anywhere, while supporting drop-in CLI/HTTP adapters for:

  • Sunbird AI Sunflower v2 / Gemma Edge (67 African languages) & USOAL Luganda TTS

  • faster-whisper / whisper.cpp / Meta MMS / Sherpa-ONNX ASR

  • Piper ONNX TTS & Ollama / llama.cpp OpenAI-compatible SLM gateways


Model Context Protocol (MCP) Server

Run SautiMesh as a zero-dependency stdio MCP tool server inside Claude Code, Cursor, Codex, or Antigravity:

sautimesh mcp

Exposes 5 native MCP tools: sautimesh_analyze_utterance, sautimesh_run_voice_turn, sautimesh_run_benchmark, sautimesh_sync_outbox, and sautimesh_export_dpg_card.


Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    Related MCP Connectors

    Related MCP Servers

    • A
      license
      Not graded
      quality
      B
      maintenance
      Exposes code-review and issue-triage tools to AI assistants over stdio, letting them evaluate unified pull-request diffs for maintainer remarks, slice diffs into categorized AST hunks, and classify GitHub issues by priority while synthesizing minimal reproduction stubs.
      1
      Apache 2.0
    • A
      license
      Not graded
      quality
      B
      maintenance
      Exposes 14 tools that let an agent query charter clauses, route and execute an 8-stage collaboration pipeline, arbitrate conflicts with cited clause IDs, enforce safety gates, run receipt self-checks, deposit and recall memory, solve symbolic anchoring constraints, and mine a 330-entry knowledge base plus semantic-field analysis. It also diagnoses image-generation prompts against a formal feature-cluster grammar, all over a zero-dependency stdio JSON-RPC interface.
      1
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Universal session & handoff layer for AI coding agents: shared task, decision, blocker and test state, checkpoints, and deterministic handoff between Claude Code, Codex, OpenCode, Cursor, Cline, pi and omp. Local SQLite, git-aware, 25 tools + 7 resources over stdio or streamable-http.
      26
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Exposes 16 local stdio MCP tools that give Codex-style clients project-isolated persistent memory, local ONNX-based semantic search, and durable task tracking that survives across sessions and concurrent clients, without executing agents, hosting a model, or contacting model providers.
      16
      MIT