Rewrite GhydraMCPServer.py from 348 to 2138 lines, implementing all 45
routes that the MCP client expects. Previously, most endpoints returned
{"error": "Not found"}, breaking tools like data_list, xrefs_list, and
memory_read.
Key changes:
- Regex-based routing table with method-aware dispatch
- Thread-safe Ghidra transactions via threading.Lock()
- Full read endpoints: functions, data, strings, memory, xrefs, structs
- Full write endpoints: rename, comment, signature, create function/data
- Analysis endpoints: callgraph traversal, dataflow, run analysis
- Jython/Python 2 compatible (no f-strings, type hints, or walrus ops)
Tested with Docker build and curl against all major endpoint groups.
MCP client integration verified working.
Refactors Docker mixin to support multiple Claude processes sharing
the same MCP server without port/container conflicts:
- PortPool class with flock-based cross-process synchronization
- Session-scoped container naming with UUID prefixes
- Docker label-based tracking for cross-process container discovery
- Automatic port allocation from pool (8192-8199)
- Cleanup mechanism for orphaned containers and stale locks
- New tools: docker_cleanup, docker_session_info
- Add ghydramcp Python package with FastMCP server implementation
- Add docker-compose.yml for easy container management
- Add Makefile with build/run targets
- Add QUICKSTART.md for getting started
- Add uv.lock for reproducible dependencies
- Switch from Java to Python scripts (avoids OSGi bundle issues)
- Update pyproject.toml with proper src layout and ruff config
- Add binaries/ and ghidra-src/ to gitignore
- Clean up Module.manifest
- Add GhydraMCPServer.py with fixed strings endpoint (Jython compatible)
- Fix strings endpoint to iterate through defined data instead of using
DefinedDataIterator.definedStrings() which isn't accessible in Jython
- Add entrypoint.sh for Docker container initialization
Separate Maven dependency resolution from compilation:
- COPY pom.xml first, run dependency:resolve (cached layer)
- COPY src second (only this invalidates on code changes)
- Build step reuses cached dependencies
Result: Code changes rebuild in ~30s instead of 3-5 min
(Ghidra download and Maven deps stay cached)
GhydraMCPServer.java imports Gson but headless scripts run in a
separate OSGi classloader that can't access extension lib JARs.
Fix: Download gson-2.13.1.jar to Framework/Generic/lib/ where it's
available to all scripts regardless of execution mode.
Closes issue documented in BUG_REPORT_HEADLESS_GSON.md
Add start_line, end_line, and max_lines parameters to decompile
functions, allowing AI models to retrieve only specific portions
of decompiled code for better context management.
Parameters:
- start_line: Start at this line number (1-indexed)
- end_line: End at this line number (inclusive)
- max_lines: Maximum lines to return (overrides end_line)
Response includes filter metadata with total_lines when filtering
is applied, helping models understand what portion they're viewing.
Examples:
- Get first 20 lines: max_lines=20
- Get lines 10-30: start_line=10, end_line=30
- Get 15 lines from line 25: start_line=25, max_lines=15
When applying a larger struct to an address, clear enough space
for the new data type rather than just the old data's length.
This prevents 'Conflicting data exists' errors when the new
type is larger than the existing data.
Fixes issue where ConfigParametersStruct couldn't be applied
due to conflicting smaller data items in the address range.
Comprehensive documentation overhaul reflecting all enhancements since fork:
- Documented new namespaced tool organization (instances_*, functions_*, data_*, structs_*, etc.)
- Added complete struct management API documentation
- Updated example usage with realistic reverse engineering workflows
- Added uvx installation method (recommended: local install for version sync)
- Updated all repository URLs to starsong-consulting
- Bumped plugin and bridge versions to v2.1.0, API version to 2010
Add endpoints and MCP tools to create, read, update, and delete struct
data types in Ghidra's data type manager. Enables programmatic definition
of complex data structures for reverse engineering workflows.
Includes pagination, category filtering, and field-level operations
(add, update by name or offset).
Improve documentation to make it clear that max_depth can be increased
for deeper call chains. This helps AI models understand when and how to
use larger depth values.
Refs #8
- Update all Ghidra JAR dependencies to 11.4.2
- Improve TransactionHelper to properly handle endTransaction return value
- Add GHIDRA_HOME environment variable support for flexible builds
- Update version references in extension.properties and MANIFEST.MF
The transaction fix now checks the return value from endTransaction() and
properly reports transaction failures, providing better error handling for
Ghidra 11.3.2+ compatibility.
Refs #7
- Update version to v2.0.0 in ApiConstants.java and bridge_mcp_hydra.py
- Create CHANGELOG v2.0.0 section with release date
- Fix Ghidra 11.3.2+ compatibility in TransactionHelper (endTransaction signature)
- Clarify instances_list vs instances_discover usage in documentation
- Remove commented-out code in pom.xml
Fixes#7Closes#5
- Fixed memory_write() endpoint to use correct ProgramEndpoints path
- Standardized all error responses to structured format with error codes
- Enhanced instances_discover() to return both new and existing instances
- Updated API version to 2005 for compatibility tracking
- Verified all bridge-to-plugin endpoint mappings are correct
- Confirmed route registration order follows proper specificity
Ready for v2.0.0 stable release after final testing.
- Modified ProgramEndpoints.java to support the name and address parameters
- Updated bridge MCP tool analysis_get_callgraph to use both parameters
- Updated tests to verify functionality with both parameters
- Added the change to CHANGELOG.md
Implemented the refactoring proposal to optimize the bridge for better MCP integration:
- Added resources for context loading (instances, functions, disassembly)
- Added prompts for common analysis patterns
- Reorganized tools into namespaced functions for better discoverability
- Implemented current working instance concept for simpler usage
- Added documentation for the namespaces-based approach
This commit fixes an issue where variable operations with paths like
/functions/by-name/FunctionName/variables/varName were not being properly
processed. The handleFunctionResource method now checks for paths that
start with 'variables/' and extracts the variable name for processing.
Added implementation to handle renaming of decompiler-generated variables.
Add documentation for the new strings endpoint in both:
- README.md: List as a feature and add example usage
- GHIDRA_HTTP_API.md: Add complete API reference with parameters and response format
The new endpoint provides:
- GET /strings endpoint with pagination and filtering
- Python bridge support via list_strings() function
- Searching of string data types across memory blocks
- Filtering options for string content
- Add comprehensive description of v2.0.0 features and capabilities
- Update API reference to include all available tools and operations
- Document HATEOAS architecture and response format
- Add detailed examples of using the new data manipulation API
- Update installation instructions for v2.0.0-beta.1
- Update Java plugin version to v2.0.0-beta.1
- Add version identifier to bridge script
- Add API version check in bridge to verify plugin compatibility
- Bridge script will now check for API version 2 compatibility
- Add handleCreateData method to Java plugin to support creating new data
- Add data type mapping to support common types like byte, word, dword, string
- Implement delete_data functionality with graceful handling of missing data
- Add proper error handling when conflicts are detected
- Add comprehensive tests for both create_data and delete_data functionality
- Add comprehensive data manipulation capabilities
- Implement separate pathways for rename-only, type-only, and combined operations
- Fix HTTP request body consumption issue in DataEndpoints
- Standardize on 'type' parameter name instead of 'dataType'
- Add thorough test coverage with dedicated test_data_update.py script
- Update API documentation to version 2 with full endpoint descriptions
- Update CHANGELOG with detailed information about data manipulation features
- Add support for setting data types and renaming data items
- Fix Java API implementation for data operation endpoints
- Create rename_data and set_data_type tools for clearer separation of concerns
- Add comprehensive test scripts for data operations
- Successfully test changing data types and naming
