Chronological feed of all changes in a project (knowledge created/updated, tasks created/updated, entries, chats, snapshots, datasets). Use this to catch up after a break: "what happened since my last session?"
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max events to return (default 50, max 200) | |
| since | No | ISO 8601 timestamp — only return events after this point (e.g. "2026-06-27T08:00:00Z") | |
| projectId | Yes | Project ID |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral context. It discloses chronological ordering, scope across many entity types, and the tool's catch-up intent. It stops short of specifying sort direction, result item shape, or read-only guarantees, but the 'feed' framing conveys the core behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core behavior and followed by a memorable use case. No filler or redundant restatement of parameter details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-style feed tool with one required parameter and fully documented optional parameters, the description provides enough context to select and invoke it. The lack of an output schema means return-structure details are not fully specified, but the high-level event list partially compensates.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents limit, since, and projectId. The description's 'since my last session' echoes the since parameter but does not add substantive meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a chronological feed of all project changes and enumerates the event categories. This distinguishes it from sibling list_* tools that target a single resource type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a concrete, memorable use case: catch up after a break and answer 'what happened since my last session?'. It does not explicitly name sibling alternatives or state when not to use it, but the intended context is unmistakable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools target distinct resources (elements, knowledge, tasks, datasets, snapshots), but a few pairs blur boundaries: create_project/init_project both create projects, and pin_knowledge/set_knowledge_relevance both mark importance for future agents. The descriptions help separate them, but misselection is possible without careful reading.
Tool names consistently use snake_case verb_noun and have solid list_/get_/search_ conventions. However creation verbs are inconsistent (add_element vs create_entry vs save_dataset vs init_project), and deletion mixes delete_entry/delete_file with remove_element, making the naming pattern less predictable than it could be.
48 tools is well above the typical well-scoped range, and the set includes many lifecycle variants (create/init/save/add, delete/remove, update/set) that inflate the count. While the server covers a broad domain, the sheer number makes it heavy and harder for an agent to navigate.
The core surfaces (projects, elements, knowledge, timeline, tasks, chats, datasets, snapshots, files) have solid create/read/update coverage, with search and session-handoff tools. Notable gaps exist: read_file references a download path for binary files that no tool provides, and there is no get_entry or delete/archive for projects, datasets, snapshots, or chat sessions.