Previously, pressing Ctrl+C while text was typed in the input prompt
would immediately exit Hermes. Now follows standard shell behavior:
- Text in buffer → Ctrl+C clears the line (like bash)
- Empty buffer → Ctrl+C exits
This means accidentally hitting Ctrl+C while composing a message just
clears the input instead of killing the session. A second Ctrl+C on
the empty prompt still exits as expected.
The TextArea uses multiline=True, so up/down arrows only moved the
cursor within text — history browsing via FileHistory was attached
but inaccessible.
Two fixes:
1. Add up/down key bindings in normal input mode that call
Buffer.auto_up()/auto_down(). These intelligently handle both:
cursor movement when editing multi-line text, and history
browsing when on the first/last line.
2. Pass append_to_history=True to buffer.reset() in the Enter
handler so messages actually get saved to ~/.hermes_history.
History persists across sessions via FileHistory. The bindings are
filtered out during clarify, approval, and sudo prompts (which
have their own up/down handlers).
After /reload-mcp updates self.agent.tools, immediately call
_persist_session() so the session JSON file at ~/.hermes/sessions/
reflects the new tools list. Without this, the tools field in the
session log would only update on the next conversation turn — if
the user quit after reloading, the log would have stale tools.
- CLI: After reload, refreshes self.agent.tools and valid_tool_names
so the model sees updated tools on its next API call
- Both CLI and Gateway: Appends a [SYSTEM: ...] message at the END
of conversation history explaining what changed (added/removed/
reconnected servers, tool count). This preserves prompt-cache for
the system prompt and earlier messages — only the tail changes.
- Gateway already creates a new AIAgent per message so tools refresh
naturally; the injected message provides context for the model
Banner integration:
- MCP Servers section in CLI startup banner between Tools and Skills
- Shows each server with transport type, tool count, connection status
- Failed servers shown in red; section hidden when no MCP configured
- Summary line includes MCP server count
- Removed raw print() calls from discovery (banner handles display)
/reload-mcp command:
- New slash command in both CLI and gateway
- Disconnects all MCP servers, re-reads config.yaml, reconnects
- Reports what changed (added/removed/reconnected servers)
- Allows adding/removing MCP servers without restarting
Resources & Prompts support:
- 4 utility tools registered per server: list_resources, read_resource,
list_prompts, get_prompt
- Exposes MCP Resources (data sources) and Prompts (templates) as tools
- Proper parameter schemas (uri for read_resource, name for get_prompt)
- Handles text and binary resource content
- 23 new tests covering schemas, handlers, and registration
Test coverage: 74 MCP tests total, 1186 tests pass overall.
When both OPENROUTER_API_KEY and OPENAI_API_KEY are set (e.g. OPENAI_API_KEY
in .bashrc), the wrong key was sent to OpenRouter causing auth failures.
Fixed key resolution order in cli.py and runtime_provider.py.
Fixes#289
Connect to external MCP servers via stdio transport, discover their tools
at startup, and register them into the hermes-agent tool registry.
- New tools/mcp_tool.py: config loading, server connection via background
event loop, tool handler factories, discovery, and graceful shutdown
- model_tools.py: trigger MCP discovery after built-in tool imports
- cli.py: call shutdown_mcp_servers in _run_cleanup
- pyproject.toml: add mcp>=1.2.0 as optional dependency
- 27 unit tests covering config, schema conversion, handlers, registration,
SDK interaction, toolset injection, graceful fallback, and shutdown
Config format (in ~/.hermes/config.yaml):
mcp_servers:
filesystem:
command: "npx"
args: ["-y", "@modelcontextprotocol/server-filesystem", "/tmp"]
The OpenAI API returns content: null on assistant messages with tool
calls. msg.get('content', '') returns None when the key exists with
value None, causing TypeError on len(), string concatenation, and
.strip() in downstream code paths.
Fixed 4 locations that process conversation messages:
- agent/auxiliary_client.py:84 — None passed to API calls
- cli.py:1288 — crash on content[:200] and len(content)
- run_agent.py:3444 — crash on None.strip()
- honcho_integration/session.py:445 — 'None' rendered in transcript
13 other instances were verified safe (already protected, only process
user/tool messages, or use the safe pattern).
Pattern: msg.get('content', '') → msg.get('content') or ''
Fixes#276
Priority is: CLI arg > config file > env var > default
(not env var > config file as the old comment stated)
The test failed because config.yaml had max_turns at both root level
and inside agent section. The test cleared agent.max_turns but the
root-level value still took precedence over the env var. Fixed the
test to clear both, and corrected the comment to match the intended
priority order.
load_cli_config() only merged keys present in its hardcoded defaults
dict, silently dropping user-added keys like platform_toolsets (saved
by 'hermes tools'), provider_routing, memory, honcho, etc.
Added a second pass to carry over all file_config keys that aren't in
defaults, so 'hermes tools' changes actually take effect in CLI mode.
The gateway was unaffected (reads YAML directly via yaml.safe_load).
Introduced a new `provider_routing` section in the CLI configuration to control how requests are routed across providers when using OpenRouter. This includes options for sorting providers by throughput, latency, or price, as well as allowing or ignoring specific providers, setting the order of provider attempts, and managing data collection policies. Updated relevant classes and documentation to support these features, enhancing flexibility in provider selection.
Updated the CLI header formatting for tool and configuration displays to center titles within their respective widths. Enhanced the display of command descriptions to include an ellipsis for longer texts, ensuring better readability. This refactor improves the overall user interface of the CLI.
Introduced a new command "/usage" in the CLI to show cumulative token usage for the current session. This includes details on prompt tokens, completion tokens, total tokens, API calls, and context state. Updated command documentation to reflect this addition. Enhanced the AIAgent class to track token usage throughout the session.
Introduced a new command "/compress" to the CLI, allowing users to manually trigger context compression on the current conversation. The method checks for sufficient conversation history and active agent status before performing compression, providing feedback on the number of messages and tokens before and after the operation. Updated command documentation accordingly.
- Enhanced Codex model discovery by fetching available models from the API, with fallback to local cache and defaults.
- Updated the context compressor's summary target tokens to 2500 for improved performance.
- Added external credential detection for Codex CLI to streamline authentication.
- Refactored various components to ensure consistent handling of authentication and model selection across the application.
Closes#77. Users can now type /verbose in the CLI to toggle verbose
mode on or off without restarting. When enabled, full tool call
parameters, results, and debug logs are shown. The agent's
verbose_logging and quiet_mode flags are updated live, and Python
logging levels are reconfigured accordingly.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Opt-in persistent cross-session user modeling via Honcho. Reads
~/.honcho/config.json as single source of truth (shared with
Claude Code, Cursor, and other Honcho-enabled tools). Zero impact
when disabled or unconfigured.
- honcho_integration/ package (client, session manager, peer resolution)
- Host-based config resolution matching claude-honcho/cursor-honcho pattern
- Prefetch user context into system prompt per conversation turn
- Sync user/assistant messages to Honcho after each exchange
- query_user_context tool for mid-conversation dialectic reasoning
- Gated activation: requires ~/.honcho/config.json with enabled=true
show_config() always checked cli-config.yaml in the project directory,
but load_cli_config() first looks at ~/.hermes/config.yaml. When the
user config existed, /config would display "cli-config.yaml (not found)"
even though configuration was loaded successfully from ~/.hermes/.
Use the same lookup order as load_cli_config and display the actual
resolved path.
max_turns used 60 as both the default and the sentinel to detect
whether the user passed the flag. This meant `--max-turns 60` was
indistinguishable from "not passed", so the env var
HERMES_MAX_ITERATIONS would silently override the explicit CLI value.
Change the default to None so any user-supplied value takes priority.
The _on_text_changed handler collapsed buffer contents into a file
reference whenever the buffer had 5+ newlines, regardless of how
those lines were entered. This meant manually typing with Alt+Enter
would trigger the paste heuristic and silently replace the user's
carefully typed input.
Track the previous buffer length and only treat a change as a paste
when more than one character is added at once (real pastes insert many
characters in a single event, while typing adds one at a time).
load_cli_config() supports both string and dict formats for the model
key (e.g. `model: "anthropic/claude-opus-4"`), but save_config_value()
assumed all intermediate keys are dicts. When the config file used the
string format, running `/model <name>` would crash with TypeError:
'str' object does not support item assignment.
Add an isinstance check so non-dict values are replaced with a fresh
dict before descending.
- Updated the description extraction logic to split on ". " (period+space) to avoid breaking on abbreviations like "e.g." or version numbers.
- Changed the method to prioritize the first line of the description, ensuring more relevant information is captured for display.
Load ~/.hermes/.env first with project root as dev fallback, and remove
redundant second load_dotenv call inside load_cli_config(). Also sets
MSWEA_GLOBAL_CONFIG_DIR so mini-swe-agent shares the same config.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Introduced a new configuration option for reasoning effort in the CLI, allowing users to specify the level of reasoning the agent should perform before responding.
- Updated the CLI and agent initialization to incorporate the reasoning configuration, enhancing the agent's responsiveness and adaptability.
- Implemented logic to load reasoning effort from environment variables and configuration files, providing flexibility in agent behavior.
- Enhanced the documentation in the example configuration file to clarify the new reasoning effort options available.
- Implemented functionality to load ephemeral prefill messages from a JSON file, enhancing few-shot priming capabilities for the agent.
- Introduced a mechanism to load an ephemeral system prompt from environment variables or configuration files, ensuring dynamic prompt adjustments at API-call time.
- Updated the CLI and agent initialization to utilize the new prefill messages and system prompt, improving the overall interaction experience.
- Enhanced configuration options with new environment variables for prefill messages and system prompts, allowing for greater customization without persistence.
- Updated the toolset ID retrieval logic in the build_welcome_banner function to use a fallback to the toolset name if the ID is not present, ensuring robustness in displaying unavailable toolsets.
- Updated the mapping of unavailable toolsets in the welcome banner from using the internal toolset ID to the toolset name for improved clarity and accuracy in display.
- Introduced a shared interrupt signaling mechanism to allow tools to check for user interrupts during long-running operations.
- Updated the AIAgent to handle interrupts more effectively, ensuring in-progress tool calls are canceled and multiple interrupt messages are combined into one prompt.
- Enhanced the CLI configuration to include container resource limits (CPU, memory, disk) and persistence options for Docker, Singularity, and Modal environments.
- Improved documentation to clarify interrupt behaviors and container resource settings, providing users with better guidance on configuration and usage.
