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MCP server · Data

Hyperterse

The agentic server framework.

77Good

Scored 6 hours ago · breakdown

About Hyperterse

Hyperterse is an MCP server published by hyperterse in the Data category: the agentic server framework.

The repository has 84 stars and 10 forks, with the last commit 5 months ago. Recent commit activity is the strongest signal that reported issues will get attention.

Install

From source
git clone https://github.com/hyperterse/hyperterse

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Security checks

Static checks derived from the repository 6 hours ago. Heuristics on the source, not an audit.

  • ✓README presentThe repository ships documentation.
  • ✓License declaredUsable under a stated license.
  • ✓Tests presentA test suite exists in the repository.
  • ✓Dependencies pinnedA lockfile pins dependency versions.
  • !No dynamic code executionSource scan found eval or shell execution. Review how tool inputs reach it before granting credentials.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

Releases

v2.5.0v2.5.0 · 21 Apr 2026A2A-compatible agents** This release aligns declarative agents with the **[A2A (Agent2Agent) protocol](https://github.com/a2aproject/a2a-go)**: new wire/executor paths, registry and HTTP surface updates, and broad test coverage. **Older,…
v2.4.0v2.4.0 · 16 Apr 2026🎉 **Declarative Agents** This release adds first-class support for **declarative AI agents** in the Hyperterse engine: discover agents from the project layout, compile them alongside tools, and run OpenAI-compatible and Google model…
v2.3.0v2.3.0 · 17 Mar 2026🎉 **Full MCP Spec + SQLite** This release completes MCP specification compliance and adds SQLite as a first-class connector. Hyperterse servers can now expose **tools**, **resources**, and **prompts** in one place — the three pillars of…
v2.2.1v2.2.1 · 12 Mar 2026Bug fixes Init command directory path** — Fixed directory references from `.agent` to `.agents` when scaffolding for Hyperterse integration with AI agents 🔧 Improvements Agent skills documentation** — Updated the documentation link in…
v2.2.0v2.2.0 · 9 Mar 2026✨ Features Smarter MCP search relevance ranking** — Search scoring now adapts to the metadata each tool actually has, improving hit quality across SQL-backed and handler-only tools 🔧 Improvements Handler-only tool relevance** —…

README


Hyperterse is an agentic server framework: one build ships agents (A2A), tools (MCP), prompts, resources, database adapters, auth, caching, and observability from a single process. You declare surfaces in config; the compiler validates and bundles them. Clients use MCP Streamable HTTP at /mcp for tools, prompts, and resources; A2A-style agent routes live at /agent/{name} when you define agents.

Where to start

The Quickstart walks through install, scaffold, and run, then optional MCP tool checks.

What Hyperterse is for

  • Running agents alongside MCP tools, prompts, and resources in one deployable service
  • Exposing database queries and custom logic as MCP tools with declarative config
  • Production Streamable HTTP for MCP and A2A routes for agents
  • TypeScript handlers and transforms where config alone is not enough

Core capabilities

  • Agents: declarative configs, tool-access policies, multi-provider models, per-agent A2A HTTP.
  • Filesystem discovery: one MCP tool per tool definition; prompts and resources follow the same discover-and-compile model (see Project structure).
  • Execution models: DB-backed tools (use + statement) or script-backed tools (handler).
  • Database adapters: PostgreSQL, MySQL, SQLite, MongoDB, Redis.
  • Per-tool auth: built-in allow_all and api_key, plus custom plugins.
  • In-memory caching: global defaults + per-tool overrides.
  • Observability: OpenTelemetry tracing/metrics + structured logging.

Quick Start

Install

curl -fsSL https://hyperterse.com/install | bash

Initialize

hyperterse init

Generated starter structure:

.
├── .hyperterse
├── .agents/
│   └── skills/
│       ├── hyperterse-docs/
│       │   └── SKILL.md
│       └── hyperterse-agents/
│           └── SKILL.md
└── app/
    └── tools/
        └── hello-world/
            ├── config.terse
            └── handler.ts

Start

hyperterse start

With live reload:

hyperterse start --watch

Verify health

curl http://localhost:8080/heartbeat

Expected response:

{ "success": true }

Optional: list MCP tools

curl -s -X POST http://localhost:8080/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "method": "tools/list",
    "id": 1
  }' | jq

By design, Hyperterse exposes two transport-layer tools:

  • search - discover project tools by natural language
  • execute - execute a project tool by name

Optional: discover project tools (search)

curl -s -X POST http://localhost:8080/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "method": "tools/call",
    "params": {
      "name": "search",
      "arguments": {
        "query": "hello world greeting"
      }
    },
    "id": 2
  }' | jq

Search hits include name, description, relevance_score, and inputs.

Execute a project tool

curl -s -X POST http://localhost:8080/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "method": "tools/call",
    "params": {
      "name": "execute",
      "arguments": {
        "tool": "hello-world",
        "inputs": { "name": "Hyperterse" }
      }
    },
    "id": 3
  }' | jq

Validate and build

hyperterse validate
hyperterse build -o dist
hyperterse serve dist/

Configuration model

Project layout

my-project/
├── .hyperterse
├── app/
│   ├── adapters/
│   │   └── primary-db.terse
│   └── tools/
│       ├── get-user/
│       │   ├── config.terse
│       │   ├── input.ts
│       │   └── output.ts
│       └── get-weather/
│           ├── config.terse
│           └── handler.ts
└── package.json

Root config (.hyperterse)

name: my-service
server:
  port: 8080
  log_level: 3
tools:
  search:
    limit: 10
  cache:
    enabled: true
    ttl: 60

Tool Examples

DB-backed tool

description: "Get user by ID"
use: primary-db
statement: |
  SELECT id, name, email
  FROM users
  WHERE id = {{ inputs.user_id }}
inputs:
  user_id:
    type: int
auth:
  plugin: api_key
  policy:
    value: "{{ env.API_KEY }}"

Script-backed tool

description: "Get weather by city"
handler: "./handler.ts"
inputs:
  city:
    type: string
auth:
  plugin: allow_all

Supported input types:

  • string
  • int
  • float
  • boolean
  • datetime

Each tool must define exactly one execution mode:

  • use (adapter-backed), or
  • handler (script-backed)

Runtime model

MCP — Streamable HTTP at /mcp (JSON-RPC 2.0): tools, prompts, resources, completion, subscriptions. See MCP transport.

A2A — JSON-RPC per agent at /agent/{agentName} (agent card, messaging, tasks, streaming). See A2A transport and Agents.

Execution pipeline:

  1. Tool resolution
  2. Authentication
  3. Input transform (optional)
  4. Execution (DB or handler)
  5. Output transform (optional)
  6. Response serialization

MCP spec compliance

Hyperterse implements the Model Context Protocol (MCP) specification 2025-11-25.

Compliance status by component:

Spec component Status
Base protocol (JSON-RPC 2.0) ✅
Lifecycle (initialize/initialized) ✅
Tools (list, call, listChanged) ✅
Resources (list, read, subscribe, updated) ✅
Prompts (list, get, listChanged) ✅
Completion (ref/prompt, ref/resource) ✅
Pagination (cursor/nextCursor) ⚠️
Tool result content types (image, audio, resource_link) ⚠️

Text content for tool results is supported; image, audio, and resource links are optional. Pagination applies when tools, prompts, or resources exceed typical small-to-medium counts.

Security notes

  • Use {{ env.VAR_NAME }} for secrets and connection strings.
  • {{ inputs.field }} statement substitution is textual; enforce strict input schemas and safe query patterns.
  • Configure tool-level auth explicitly for production use.

Documentation map

Contributing

  1. Fork the repo.
  2. Create a feature branch.
  3. Add or update tests.
  4. Run validation locally.
  5. Open a PR.

See CONTRIBUTING.md and CODE_OF_CONDUCT.md.


README fetched from the repository 6 hours ago. The original is authoritative.

Questions

About Hyperterse

How do I install Hyperterse?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is Hyperterse safe to use with an AI agent?

Its trust score is 77 out of 100 (good). It passes 4 of the 6 static security checks run so far; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Hyperterse still maintained?

Yes — the latest release is v2.5.0 (21 Apr 2026), and the last commit was 5 months ago. The repository has 84 stars.