agent-block-0.10.0 is not a library.

agent-block

Single-purpose agent building block with built-in mesh communication.

What is agent-block?

A headless agent runtime. Each agent runs as a single process, executes its task, then exits. No rich interactive TUI, no sub-agent orchestration — orchestration belongs to the caller (shell, A2A, CI, etc.).

agent-block handles the infrastructure that individual agents shouldn't have to — mesh connectivity (A2A), MCP server management, LLM API access — so that Lua code focuses purely on domain logic.

Think of it like Envoy for agents: the process itself is simple, but the communication layer is fully capable.

Design Decisions

Single run — One process, one task, one exit. Orchestration belongs to the caller (shell, A2A, CI, etc.), not inside the agent
Headless — No terminal UI. Agents are composed via A2A/mesh protocols, not interactive prompts
Runtime owns the protocol — Mesh, MCP, and HTTP are provided by the runtime. Lua code never deals with connection management or wire formats
Lua for logic, Rust for plumbing — Domain logic in Lua. VM, networking, and protocol handling in Rust

Architecture

┌─────────────────────────────────────────────┐
│              agent-block (binary)            │
│                                             │
│  ┌─────────┐  ┌──────────┐  ┌───────────┐  │
│  │ mlua-isle│  │ mesh-sdk │  │ llm-client│  │
│  │ (Lua VM) │  │ (relay)  │  │ (API)     │  │
│  └────┬─────┘  └────┬─────┘  └─────┬─────┘  │
│       │             │              │         │
│  ─────┴─────────────┴──────────────┴─────── │
│              Lua Stdlib Bridge               │
│  mesh.send / mesh.on / llm.chat / fs.read   │
│  tool.register / tool.call / log.* / env.*  │
│  mcp.connect / mcp.call / mcp.list_tools    │
└─────────────────────────────────────────────┘
         ↕ WebSocket              ↕ stdio
┌─────────────────┐    ┌──────────────────┐
│   agent-mesh     │    │  MCP Servers     │
│   relay          │    │  (outline-mcp)   │
└─────────────────┘    └──────────────────┘

Usage

# Basic
agent-block --script scripts/hello.lua

# With project context
agent-block --script scripts/test_fcloop.lua --project .

# With mesh
ANTHROPIC_API_KEY=... agent-block --script my_agent.lua --relay ws://localhost:9090/ws

MCP Echo Harness

A self-contained reference MCP server for smoke-testing the agent-block MCP client bridge. Exposes tools, resources, prompts, logging, and sampling over stdio or HTTP.

# stdio (default) — connect via mcp.connect("echo", "target/debug/examples/echo_mcp_server", {})
cargo run --example echo_mcp_server

# HTTP on an ephemeral port — prints ECHO_MCP_URL=http://127.0.0.1:<port>/mcp
cargo run --example echo_mcp_server -- --transport http --port 0

# Also emit 5 log notifications (1-second intervals) and attempt a sampling round-trip
cargo run --example echo_mcp_server -- --transport http --port 0 --emit-logs --request-sampling

Verify from Lua (requires the server to be running with --transport http):

local url = os.getenv("ECHO_MCP_URL")
mcp.connect_http("echo", url)
print(mcp.list_tools("echo"))         -- 2 tools: echo, slow_echo
print(mcp.list_resources("echo"))     -- 2 resources: text://hello, text://note
print(mcp.list_prompts("echo"))       -- 1 prompt: greet
-- call slow_echo to exercise progress notifications
mcp.on_progress("echo", function(tok, prog, total, msg)
    print("progress", prog, total, msg)
end)
print(mcp.call("echo", "slow_echo", { msg = "hi", steps = 3 }))

See examples/verify_echo_harness.lua for the full verification script.

Lua API

llm.*

llm.chat(messages, opts) — LLM call (Anthropic Messages API)

tool.*

tool.register(name, schema, handler) — Register a tool
tool.call(name, input) — Call a registered tool
tool.list() — List registered tool names
tool.schema() — Anthropic tools-format schema array

mcp.*

mcp.connect(name, command, args) — Spawn MCP server over stdio + initialize handshake
mcp.connect_http(name, url, opts) — Connect to an MCP server over HTTP transport. opts.transport = "sse" | "http" (default "http" = Streamable HTTP; "sse" = SSE). opts.headers table is forwarded as request headers.
mcp.call(name, tool_name, arguments) — Call an MCP tool
mcp.list_tools(name) — List available tools
mcp.list_resources(name) — List resources exposed by the server. Returns { ok=true, resources=[{uri, name, description, mimeType, ...}] }.
mcp.read_resource(name, uri) — Read a resource by URI. Returns { ok=true, contents=[{uri, mimeType, text|blob}] }.
mcp.list_prompts(name) — List prompt templates exposed by the server. Returns { ok=true, prompts=[{name, description, arguments}] }.
mcp.get_prompt(name, prompt_name, args) — Retrieve a rendered prompt template. Returns { ok=true, description, messages=[{role, content}] }.
mcp.on_progress(name, handler) — Register a per-server progress notification callback. handler(token, progress, total, message) is called for each notifications/progress event from the named server. Handler must be a pure Lua function.
mcp.on_log(name, handler) — Register a per-server log notification callback. handler(level, logger, data) is called for each notifications/message event from the named server. When no handler is registered the notification is forwarded to the Rust tracing target "lua" at the corresponding level (debug/info/notice/warning/ error/critical/alert/emergency). Handler must be a pure Lua function.
mcp.cancel(name, request_id) — Send a notifications/cancelled notification to the named server for the given request_id. Also fired automatically when mcp.call times out. Explicit use is only needed for manual cancellation flows.
mcp.set_sampling_handler(server_name, handler) — Register a per-server Lua function to respond to sampling/createMessage requests from the MCP server. handler(params) receives the CreateMessageRequest table and must return a table matching CreateMessageResult ({ model, stop_reason, role, content }). When no handler is registered the server receives method_not_found.
mcp.server_info(name) — Return the server's InitializeResult as a Lua table. Returns { ok=true, server_info={serverInfo, capabilities, ...} } on success. Useful for inspecting which MCP capability groups (resources, prompts, tools, etc.) a server declares. Returns { ok=false, error="..." } if the server is not connected.
mcp.disconnect(name) — Disconnect server

mesh.*

mesh.send(agent_id, payload) — Synchronous send (raises Lua error on failure)
mesh.request(agent_id, payload) — Request-response
mesh.agent_id() — Own AgentId

std.fs.* (mlua-batteries)

std.fs.read(path), std.fs.write(path, content), std.fs.glob(pattern), std.fs.exists(path)
std.fs.walk(dir), std.fs.copy(src, dst), std.fs.mkdir(path), std.fs.remove(path)
std.fs.is_file(path), std.fs.is_dir(path), std.fs.read_binary(path), std.fs.write_binary(path, bytes)

sh.*

sh.exec(cmd, opts) — Execute a shell command

std.json.* (mlua-batteries)

std.json.encode(value), std.json.decode(str), std.json.encode_pretty(value)

std.env.* (mlua-batteries + agent-block extensions)

std.env.get(key), std.env.set(key, value), std.env.get_or(key, default), std.env.home()
std.env.agent_id(), std.env.project_root() — agent-block specific

std.path.* / std.time.* (mlua-batteries)

std.path.join(...), std.path.basename(path), std.path.dirname(path)
std.time.now(), std.time.sleep(secs), std.time.measure(fn)

agent (StdPkg — `require("agent")`)

Built-in ReAct loop module. Available without any path configuration after cargo install.

local agent = require("agent")

local result = agent.run({
    prompt  = "List files in the current directory and summarise them.",
    system  = "You are a helpful assistant.",           -- optional
    model   = "claude-haiku-4-5-20251001",             -- optional, env ANTHROPIC_MODEL as fallback
    max_tokens       = 4096,                            -- per-request token limit
    max_iterations   = 20,                              -- loop iteration cap
    max_tokens_budget = 50000,                          -- total token budget (nil = unlimited)
    timeout          = 120,                             -- HTTP timeout in seconds
    mcp_servers = {                                     -- optional MCP servers to connect
        { name = "outline", command = "outline-mcp", args = {} },
        -- HTTP/SSE form: use `url` instead of `command`
        { name = "remote", url = "https://example.com/mcp",
          transport_opts = { transport = "sse" } },     -- transport = "sse" | "http" (default "http")
    },
    sampling = function(params) ... end,                -- optional: called for sampling/createMessage
                                                        -- from every connected MCP server
    -- Anthropic server-side context editing (default ON). Pass `false` to opt out,
    -- or pass a full override table (replaces the default entirely).
    context_management        = true,                   -- default true; false disables beta header + body
    context_management_config = {                       -- default: trigger 80K, keep 3, clear_at_least 10K
        edits = {
            {
                type           = "clear_tool_uses_20250919",
                trigger        = { type = "input_tokens", value = 80000 },
                keep           = { type = "tool_uses",    value = 3 },
                clear_at_least = { type = "input_tokens", value = 10000 },
            },
        },
    },
    on_turn = function(info)                            -- optional per-turn callback
        print("turn", info.turn_number, "#tools", #info.tool_calls)
        -- info.context_management is present only on turns where the server fired
        -- an edit; nil-guard before indexing applied_edits.
        if info.context_management and info.context_management.applied_edits then
            for _, edit in ipairs(info.context_management.applied_edits) do
                print("  edit:", edit.type, "cleared", edit.cleared_tool_uses, "tool_uses")
            end
        end
    end,
    extra_tools = {},                                   -- optional extra Anthropic tool defs
})

if result.ok then
    print(result.content)
else
    print("error:", result.error)
end
-- result fields: ok, content, usage{input_tokens,output_tokens,total_tokens}, num_turns, error, messages

Provider Switching

By default agent.run uses the Anthropic Messages API. Pass provider = "openai" to route to any OpenAI-compatible endpoint (vLLM, llama.cpp, OpenRouter, RunPod, etc.):

-- Anthropic (default) — requires ANTHROPIC_API_KEY
local result = agent.run({ prompt = "Hello", model = "claude-haiku-4-5-20251001" })

-- OpenAI — requires OPENAI_API_KEY (or opts.api_key)
local result = agent.run({
    prompt  = "Hello",
    provider = "openai",
    model   = "gpt-4o-mini",
})

-- Local vLLM / llama.cpp / RunPod — custom base_url
local result = agent.run({
    prompt   = "Hello",
    provider = "openai",
    base_url = "http://localhost:8080/v1",
    model    = "Qwen/Qwen3-0.6B",
    api_key  = "token-abc123",           -- or api_key_env = "MY_KEY"
})

Environment variables used per provider:

provider	default key env	override via
`anthropic`	`ANTHROPIC_API_KEY`	`opts.api_key` / `opts.api_key_env`
`openai`	`OPENAI_API_KEY`	`opts.api_key` / `opts.api_key_env`

opts.base_url overrides the endpoint root. Default for openai is https://api.openai.com/v1.

cache_control, context_management, and context_management_config are Anthropic-only: they are operative when provider="anthropic" (or unset) and emit a warn-level log message then are ignored when provider="openai".

Key behaviours:

MCP servers listed in mcp_servers are connected automatically and disconnected on exit (even on error).
Each entry may use the stdio form { name, command, args } or the HTTP form { name, url, transport_opts }. Both forms can coexist in the same list.
Pass sampling = fn in agent.run opts to register a single Lua function as the sampling/createMessage handler for every connected MCP server (mcp.set_sampling_handler is called per server automatically).
Pass enable_resources = true in agent.run opts to automatically register {server}__mcp_list_resources and {server}__mcp_read_resource as LLM-callable tools for each connected server that declares the resources capability. Default false. If a server does not declare resources, the opt-in is silently skipped (logged at info).
Pass enable_prompts = true in agent.run opts to automatically register {server}__mcp_list_prompts and {server}__mcp_get_prompt as LLM-callable tools for each connected server that declares the prompts capability. Default false. Capability check and silent skip apply the same way as enable_resources.
Pass on_progress = fn(ev) in agent.run opts to receive progress notifications from all connected MCP servers. The callback is called with an envelope table { type="progress", server, token, progress, total, message }. No capability gate — all servers are registered. User callback errors are swallowed and logged at warn.
Pass progress_to_log = true in agent.run opts to bridge progress notifications to log.info automatically. Ignored when on_progress is also set (callback takes priority). Default false.
Pass on_log = fn(ev) in agent.run opts to receive log notifications from servers that declare the logging capability. The callback is called with an envelope table { type="log", server, level, logger, data }. Servers without logging capability are silently skipped (logged at info). User callback errors are swallowed and logged at warn.
Pass log_to_stderr = true in agent.run opts to bridge server log notifications to log.debug|info|warn|error automatically. Ignored when on_log is also set (callback takes priority). Logging capability gate applies the same way as on_log. Default false.
MCP tool names are namespaced as server_name__tool_name to avoid collisions.
Tool dispatch: MCP tools via mcp.call(), registered Lua tools via tool.call().
Never throws — all errors returned as { ok=false, error="..." }.
Context editing is on by default: once the conversation crosses ~80K input tokens, Anthropic evicts all but the most recent 3 tool-use / tool-result pairs server-side so the loop can keep running. Works on Sonnet 4 / Sonnet 4.5 / Haiku 4.5 / Opus 4 / 4.1 / 4.5. Pass context_management = false to disable, or context_management_config = { edits = { ... } } to replace the default entirely (the whole table is forwarded as body.context_management; no partial merge).
on_turn(info) gains an additive info.context_management field that forwards the raw response.context_management from Anthropic ({ applied_edits = { { type, cleared_tool_uses, cleared_input_tokens }, ... } }). The field is absent on turns where the server did not fire any edit — nil-guard before indexing.
The blocks/ directory is embedded in the binary; place a local blocks/agent/init.lua in the project root to override.
LLM dump logging is safe-by-default and ENV-driven:
- AGENT_BLOCK_LLM_DUMP=off|meta|full (default off)
- when unset, RUST_LOG containing debug or trace enables meta
- full is downgraded to meta when AGENT_BLOCK_ENV=prod|production unless AGENT_BLOCK_LLM_DUMP_ALLOW_PROD=true
- request auth headers (x-api-key / authorization) are always redacted in dump logs
- log lines use fixed-order key=value format with a unique marker (prefix=ab.obs component=llm); legacy prefix=ab.llm lines are also emitted for compatibility
- meta includes call correlation and runtime signals (call, turn, iter, latency_ms, stop_reason, tool_uses, token usage, context edit count)
- optional agent.run({ log_meta = { trace_id, agent_id, agent_name, run_id } }) appends external context to dump lines (same keys can also come from AGENT_BLOCK_TRACE_ID, AGENT_BLOCK_AGENT_ID, AGENT_BLOCK_AGENT_NAME, AGENT_BLOCK_RUN_ID)

lshape (Vendored package — `require("lshape")`)

lshape is vendored under blocks/lshape/ so scripts can use schema validation and LuaCATS generation without external installation.

local lshape = require("lshape")
local T = lshape.t
local User = T.shape({ name = T.string, age = T.number })
local ok, why = lshape.check.check({ name = "Ada", age = 36 }, User)
assert(ok, why)

log.*

log.info/warn/error/debug(msg)

License

Licensed under either of

Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)

at your option.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.

agent-block 0.10.0